Richard G. Baraniuk

594 papers A* 37A 12B 48C 4Misc 52Journal 319Unranked 117

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models. EACL (Findings) Naiming Liu, Richard G. Baraniuk, Shashank Sonkar
2026	J	`jnl`	Circuit Complexity of Hierarchical Knowledge Tracing and Implications for Log-Precision Transformers. CoRR Naiming Liu, Richard G. Baraniuk, Shashank Sonkar
2026	J	`jnl`	Leakage and Second-Order Dynamics Improve Hippocampal RNN Replay. CoRR Josue Casco-Rodriguez, Nanda H. Krishna, Richard G. Baraniuk
2026	J	`jnl`	Learning Context Matters: Measuring and Diagnosing Personalization Gaps in LLM-Based Instructional Design. CoRR Johaun Hatchett, Debshila Basu Mallick, Brittany C. Bradford, Richard G. Baraniuk
2026	J	`jnl`	MetaCLASS: Metacognitive Coaching for Learning with Adaptive Self-regulation Support. CoRR Naiming Liu, Richard G. Baraniuk, Shashank Sonkar
2026	J	`jnl`	Scalable Generation and Validation of Isomorphic Physics Problems with GenAI. CoRR Naiming Liu, Leo Murch, Spencer Moore, Tong Wan, Shashank Sonkar, Richard G. Baraniuk, Zhongzhou Chen
2025	A	`conf`	Atomic Learning Objectives and LLMs Labeling: A High-Resolution Approach for Physics Education. LAK Naiming Liu, Shashank Sonkar, Debshila Basu Mallick, Richard G. Baraniuk, Zhongzhou Chen
2025	J	`jnl`	CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models. CoRR Naiming Liu, Richard G. Baraniuk, Shashank Sonkar
2025	J	`jnl`	Do LLMs Make Mistakes Like Students? Exploring Natural Alignment between Language Models and Human Error Patterns. CoRR Naiming Liu, Shashank Sonkar, Richard G. Baraniuk
2025	—	`conf`	Do LLMs Make Mistakes Like Students? Exploring Natural Alignments Between Language Models and Human Error Patterns. AIED (4) Naiming Liu, Shashank Sonkar, Richard G. Baraniuk
2025	Misc	`conf`	Estimating the Number and Locations of Boundaries in Reverberant Environments with Deep Learning. ICASSP Toros Arikan, Luca M. Chackalackal, Fatima Ahsan, Konrad Tittel, Andrew C. Singer, Gregory W. Wornell, Richard G. Baraniuk
2025	J	`jnl`	GrokAlign: Geometric Characterisation and Acceleration of Grokking. CoRR Thomas Walker, Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2025	J	`jnl`	Improving Routing in Sparse Mixture of Experts with Graph of Tokens. CoRR Tam Minh Nguyen, Ngoc N. Tran, Khai Nguyen, Richard G. Baraniuk
2025	J	`jnl`	Learning Context: A Unified Framework and Roadmap for Context-Aware AI in Education. CoRR Naiming Liu, Brittany C. Bradford, Johaun Hatchett, Gabriel Diaz, Lorenzo Luzi, Zichao Wang, Debshila Basu Mallick, Richard G. Baraniuk
2025	—	`conf`	Many-Shot Regurgitation Prompting. AIED (5) Shashank Sonkar, Naiming Liu, Richard G. Baraniuk
2025	A*	`conf`	Mitigating over-Exploration in Latent Space Optimization using les. ICML Omer Ronen, Ahmed Imtiaz Humayun, Richard G. Baraniuk, Randall Balestriero, Bin Yu
2025	J	`jnl`	Neon: Negative Extrapolation From Self-Training Improves Image Generation. CoRR Sina Alemohammad, Zhangyang Wang, Richard G. Baraniuk
2025	J	`jnl`	Rates and architectures for learning geometrically non-trivial operators. CoRR T. Mitchell Roddenberry, Leo Tzou, Ivan Dokmanic, Maarten V. de Hoop, Richard G. Baraniuk
2025	J	`jnl`	SaFARi: State-Space Models for Frame-Agnostic Representation. CoRR Hossein Babaei, Mel White, Sina Alemohammad, Richard G. Baraniuk
2025	J	`jnl`	SaFARi: State-Space Models for Frame-Agnostic Representation. Trans. Mach. Learn. Res. Hossein Babaei, Mel White, Sina Alemohammad, Richard G. Baraniuk
2025	J	`jnl`	The Imitation Game for Educational AI. CoRR Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk
2025	J	`jnl`	The Importance of Teaching Logic to Computer Scientists and Electrical Engineers. ACM Trans. Comput. Educ. Paul M. Mayer, Richard G. Baraniuk
2025	—	`conf`	Training LLM-Based Tutors to Improve Student Learning Outcomes in Dialogues. AIED (1) Alexander Scarlatos, Naiming Liu, Jaewook Lee, Richard G. Baraniuk, Andrew S. Lan
2025	J	`jnl`	Training LLM-based Tutors to Improve Student Learning Outcomes in Dialogues. CoRR Alexander Scarlatos, Naiming Liu, Jaewook Lee, Richard G. Baraniuk, Andrew S. Lan
2025	—	`conf`	Turing-Like Test for Personalized Educational AI. AIED (6) Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk
2025	J	`jnl`	W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling. CoRR Hossein Babaei, Mel White, Richard G. Baraniuk
2025	J	`jnl`	WaLRUS: Wavelets for Long-range Representation Using SSMs. CoRR Hossein Babaei, Mel White, Sina Alemohammad, Richard G. Baraniuk
2024	J	`jnl`	A Primal-Dual Framework for Transformers and Neural Networks. CoRR Tan M. Nguyen, Tam Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2024	J	`jnl`	Asymptotics of the Sketched Pseudoinverse. SIAM J. Math. Data Sci. Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani
2024	J	`jnl`	Atomic Learning Objectives Labeling: A High-Resolution Approach for Physics Education. CoRR Naiming Liu, Shashank Sonkar, Debshila Basu Mallick, Richard G. Baraniuk, Zhongzhou Chen
2024	—	`conf`	Automated Long Answer Grading with RiceChem Dataset. AIED (1) Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk
2024	J	`jnl`	Automated Long Answer Grading with RiceChem Dataset. CoRR Shashank Sonkar, Kangqi Ni, Lesa Tran Lu, Kristi Kincaid, John S. Hutchinson, Richard G. Baraniuk
2024	J	`jnl`	Boomerang: Local sampling on image manifolds using diffusion models. Trans. Mach. Learn. Res. Lorenzo Luzi, Paul M. Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard G. Baraniuk
2024	A	`conf`	Code Soliloquies for Accurate Calculations in Large Language Models. LAK Shashank Sonkar, Xinghe Chen, Myco Le, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
2024	J	`jnl`	Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust. IEEE Trans. Neural Networks Learn. Syst. Hossein Babaei, Sina Alemohammad, Richard G. Baraniuk
2024	A*	`conf`	Deep Networks Always Grok and Here is Why. ICML Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2024	J	`jnl`	Deep Networks Always Grok and Here is Why. CoRR Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2024	J	`jnl`	DeepTensor: Low-Rank Tensor Decomposition With Deep Network Priors. IEEE Trans. Pattern Anal. Mach. Intell. Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan, Richard G. Baraniuk
2024	J	`jnl`	Estimating the Number and Locations of Boundaries in Reverberant Environments with Deep Learning. CoRR Toros Arikan, Luca M. Chackalackal, Fatima Ahsan, Konrad Tittel, Andrew C. Singer, Gregory W. Wornell, Richard G. Baraniuk
2024	A*	`conf`	Implicit Neural Representations and the Algebra of Complex Wavelets. ICLR T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk
2024	J	`jnl`	LLM-based Cognitive Models of Students with Misconceptions. CoRR Shashank Sonkar, Xinghe Chen, Naiming Liu, Richard G. Baraniuk, Mrinmaya Sachan
2024	A*	`conf`	Learning Transferable Features for Implicit Neural Representations. NeurIPS Kushal Kardam Vyas, Ahmed Imtiaz Humayun, Aniket Dashpute, Richard G. Baraniuk, Ashok Veeraraghavan, Guha Balakrishnan
2024	J	`jnl`	Learning Transferable Features for Implicit Neural Representations. CoRR Kushal Vyas, Ahmed Imtiaz Humayun, Aniket Dashpute, Richard G. Baraniuk, Ashok Veeraraghavan, Guha Balakrishnan
2024	J	`jnl`	MalAlgoQA: A Pedagogical Approach for Evaluating Counterfactual Reasoning Abilities. CoRR Naiming Liu, Shashank Sonkar, Myco Le, Richard G. Baraniuk
2024	—	`conf`	MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education. EMNLP (Findings) Shashank Sonkar, Naiming Liu, Myco Le, Richard G. Baraniuk
2024	J	`jnl`	Many-Shot Regurgitation (MSR) Prompting. CoRR Shashank Sonkar, Richard G. Baraniuk
2024	—	`conf`	Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. AIED (1) Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
2024	J	`jnl`	Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. CoRR Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
2024	J	`jnl`	MazeNet: An Accurate, Fast, and Scalable Deep Learning Solution for Steiner Minimum Trees. CoRR Gabriel Díaz-Ramos, Toros Arikan, Richard G. Baraniuk
2024	J	`jnl`	On the Geometry of Deep Learning. CoRR Randall Balestriero, Ahmed Imtiaz Humayun, Richard G. Baraniuk
2024	A*	`conf`	PIDformer: Transformer Meets Control Theory. ICML Tam Minh Nguyen, César A. Uribe, Tan Minh Nguyen, Richard G. Baraniuk
2024	J	`jnl`	PIDformer: Transformer Meets Control Theory. CoRR Tam Nguyen, César A. Uribe, Tan M. Nguyen, Richard G. Baraniuk
2024	—	`conf`	Pedagogical Alignment of Large Language Models. EMNLP (Findings) Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk
2024	J	`jnl`	Pedagogical Alignment of Large Language Models. CoRR Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk
2024	J	`jnl`	Regressive Side Effects of Training Language Models to Mimic Student Misconceptions. CoRR Shashank Sonkar, Naiming Liu, Richard G. Baraniuk
2024	J	`jnl`	Removing Bias from Maximum Likelihood Estimation with Model Autophagy. CoRR Paul M. Mayer, Lorenzo Luzi, Ali Siahkoohi, Don H. Johnson, Richard G. Baraniuk
2024	J	`jnl`	ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks. CoRR Omer Ronen, Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk, Bin Yu
2024	A*	`conf`	Self-Consuming Generative Models Go MAD. ICLR Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
2024	J	`jnl`	Self-Improving Diffusion Models with Synthetic Data. CoRR Sina Alemohammad, Ahmed Imtiaz Humayun, Shruti Agarwal, John P. Collomosse, Richard G. Baraniuk
2024	—	`conf`	Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning. EMNLP (Findings) Shashank Sonkar, Naiming Liu, Richard G. Baraniuk
2024	J	`jnl`	Synthetic Context Generation for Question Generation. CoRR Naiming Liu, Zichao Wang, Richard G. Baraniuk
2024	J	`jnl`	The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. SIAM J. Math. Data Sci. Yehuda Dar, Daniel LeJeune, Richard G. Baraniuk
2024	Misc	`conf`	Titan: Bringing the Deep Image Prior to Implicit Representations. ICASSP Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk
2024	J	`jnl`	[Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. CoRR Josue Casco-Rodriguez, Caleb Kemere, Richard G. Baraniuk
2023	A	`conf`	A Blessing of Dimensionality in Membership Inference through Regularization. AISTATS Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk
2023	—	`conf`	A Case Study using Large Language Models to Generate Metadata for Math Questions. LLM@AIED Katie Bainbridge, Candace A. Walkington, Armon Ibrahim, Iris Zhong, Debshila Basu Mallick, Julianna Washington, Richard G. Baraniuk
2023	A*	`conf`	A Primal-Dual Framework for Transformers and Neural Networks. ICLR Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2023	Misc	`conf`	A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. ICASSP Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Duy Khuong Nguyen, Dung D. Le, Hung Tran-The, Nhat Ho, Stanley J. Osher, Richard G. Baraniuk
2023	J	`jnl`	CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles. CoRR Shashank Sonkar, Lucy Liu, Debshila Basu Mallick, Richard G. Baraniuk
2023	—	`conf`	CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. EMNLP (Findings) Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
2023	J	`jnl`	Code Soliloquies for Accurate Calculations in Large Language Models. CoRR Shashank Sonkar, Myco Le, Xinghe Chen, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk
2023	—	`conf`	Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models. LLM@AIED Shashank Sonkar, Richard G. Baraniuk
2023	J	`jnl`	Deduction under Perturbed Evidence: Probing Student Simulation Capabilities of Large Language Models. CoRR Shashank Sonkar, Richard G. Baraniuk
2023	A	`conf`	Evaluating generative networks using Gaussian mixtures of image features. WACV Lorenzo Luzi, Carlos Ortiz Marrero, Nile Wynar, Richard G. Baraniuk, Michael J. Henry
2023	B	`conf`	Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Klinton Bicknell, Jeremy Roschelle, Ben Motz, Danielle S. McNamara, Richard G. Baraniuk, Debshila Basu Mallick, René F. Kizilcec, Ryan Baker, Stephen Fancsali, April Murphy
2023	J	`jnl`	Implicit Neural Representations and the Algebra of Complex Wavelets. CoRR T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk
2023	J	`jnl`	Investigating the Role of Feed-Forward Networks in Transformers Using Parallel Attention and Feed-Forward Net Design. CoRR Shashank Sonkar, Richard G. Baraniuk
2023	—	`conf`	MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. SustaiNLP Shashank Sonkar, Zichao Wang, Richard G. Baraniuk
2023	A*	`conf`	Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. NeurIPS Tam Nguyen, Tan Nguyen, Richard G. Baraniuk
2023	J	`jnl`	Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. CoRR Tam Nguyen, Tan M. Nguyen, Richard G. Baraniuk
2023	—	`conf`	MultiQG-TI: Towards Question Generation from Multi-modal Sources. BEA@ACL Zichao Wang, Richard G. Baraniuk
2023	J	`jnl`	MultiQG-TI: Towards Question Generation from Multi-modal Sources. CoRR Zichao Wang, Richard G. Baraniuk
2023	J	`jnl`	Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions. CoRR Naiming Liu, Shashank Sonkar, Zichao Wang, Simon Woodhead, Richard G. Baraniuk
2023	J	`jnl`	Perspectives on the State and Future of Deep Learning - 2023. CoRR Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson
2023	A*	`conf`	Retrieval-based Controllable Molecule Generation. ICLR Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar
2023	B	`conf`	Secure Education and Learning Research at Scale with OpenStax Kinetic. L@S Debshila Basu Mallick, Brittany C. Bradford, Richard G. Baraniuk
2023	J	`jnl`	Self-Consuming Generative Models Go MAD. CoRR Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
2023	A*	`conf`	SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CVPR Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk
2023	J	`jnl`	SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CoRR Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk
2023	—	`conf`	Towards the Future of AI-Augmented Human Tutoring in Math Learning. AIED (Posters/Late Breaking Results/...) Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott A. Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing
2023	J	`jnl`	Training Dynamics of Deep Network Linear Regions. CoRR Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2023	B	`conf`	Unlocking Financial Success: Empowering Higher Ed Students and Developing Financial Literacy Interventions at Scale. L@S Brittany C. Bradford, Debshila Basu Mallick, Richard G. Baraniuk
2023	J	`jnl`	Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Trans. Signal Process. Fernando Gama, Nicolas Zilberstein, Martin Sevilla, Richard G. Baraniuk, Santiago Segarra
2023	A*	`conf`	WIRE: Wavelet Implicit Neural Representations. CVPR Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk
2023	J	`jnl`	WIRE: Wavelet Implicit Neural Representations. CoRR Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk
2022	J	`jnl`	A Visual Tour Of Current Challenges In Multimodal Language Models. CoRR Shashank Sonkar, Naiming Liu, Richard G. Baraniuk
2022	J	`jnl`	Asymptotics of the Sketched Pseudoinverse. CoRR Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani
2022	—	`conf`	Automated Scoring for Reading Comprehension via In-context BERT Tuning. AIED (1) Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
2022	J	`jnl`	Automated Scoring for Reading Comprehension via In-context BERT Tuning. CoRR Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
2022	J	`jnl`	Batch Normalization Explained. CoRR Randall Balestriero, Richard G. Baraniuk
2022	J	`jnl`	Benign Overparameterization in Membership Inference with Early Stopping. CoRR Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk
2022	J	`jnl`	Boomerang: Local sampling on image manifolds using diffusion models. CoRR Lorenzo Luzi, Ali Siahkoohi, Paul M. Mayer, Josue Casco-Rodriguez, Richard G. Baraniuk
2022	A*	`conf`	Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
2022	Misc	`conf`	DeepHull: Fast Convex Hull Approximation in High Dimensions. ICASSP Randall Balestriero, Zichao Wang, Richard G. Baraniuk
2022	J	`jnl`	DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors. CoRR Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan, Richard G. Baraniuk
2022	J	`jnl`	Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. SIAM J. Math. Data Sci. Yehuda Dar, Richard G. Baraniuk
2022	J	`jnl`	Extreme Compressed Sensing of Poisson Rates From Multiple Measurements. IEEE Trans. Signal Process. Pavan K. Kota, Daniel LeJeune, Rebekah A. Drezek, Richard G. Baraniuk
2022	J	`jnl`	Foveated Thermal Computational Imaging in the Wild Using All-Silicon Meta-Optics. CoRR Vishwanath Saragadam, Zheyi Han, Vivek Boominathan, Luocheng Huang, Shiyu Tan, Johannes E. Fröch, Karl F. Böhringer, Richard G. Baraniuk, Arka Majumdar, Ashok Veeraraghavan
2022	A*	`conf`	Improving Transformers with Probabilistic Attention Keys. ICML Tam Minh Nguyen, Tan Minh Nguyen, Dung D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
2022	J	`jnl`	MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. CoRR Shashank Sonkar, Zichao Wang, Richard G. Baraniuk
2022	—	`conf`	MINER: Multiscale Implicit Neural Representation. ECCV (23) Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan
2022	J	`jnl`	MINER: Multiscale Implicit Neural Representations. CoRR Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan
2022	A*	`conf`	MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. ICLR Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2022	J	`jnl`	Max-Affine Spline Insights Into Deep Network Pruning. Trans. Mach. Learn. Res. Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard G. Baraniuk
2022	—	`conf`	Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. CoRR Tan M. Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer. Comput. Medical Imaging Graph. David J. Brenes, C. J. Barberan, Brady Hunt, Sonia G. Parra, Mila P. Salcedo, Júlio C. Possati-Resende, Miriam L. Cremer, Philip E. Castle, José H. T. G. Fregnani, Mauricio Maza, Kathleen M. Schmeler, Richard G. Baraniuk, Rebecca R. Richards-Kortum
2022	Misc	`conf`	NFT-K: Non-Fungible Tangent Kernels. ICASSP Sina Alemohammad, Hossein Babaei, C. J. Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk
2022	—	`conf`	NeuroView-RNN: It's About Time. FAccT C. J. Barberan, Sina Alemohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk
2022	J	`jnl`	NeuroView-RNN: It's About Time. CoRR C. J. Barberan, Sina Alemohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk
2022	Misc	`conf`	No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. ICASSP Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
2022	J	`jnl`	No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. CoRR Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
2022	J	`jnl`	On Local Distributions in Graph Signal Processing. CoRR T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra
2022	J	`jnl`	On Local Distributions in Graph Signal Processing. IEEE Trans. Signal Process. T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra
2022	J	`jnl`	Open-Ended Knowledge Tracing. CoRR Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2022	A*	`conf`	Open-ended Knowledge Tracing for Computer Science Education. EMNLP Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2022	J	`jnl`	Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks. CoRR Yehuda Dar, Lorenzo Luzi, Richard G. Baraniuk
2022	A*	`conf`	Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. NeurIPS Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk
2022	J	`jnl`	Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. CoRR Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk
2022	A*	`conf`	Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CVPR Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2022	J	`jnl`	Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CoRR Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2022	J	`jnl`	Recurrent Scattering Network Detects Metastable Behavior in Polyphonic Seismo-Volcanic Signals for Volcano Eruption Forecasting. IEEE Trans. Geosci. Remote. Sens. Ángel Bueno Rodríguez, Randall Balestriero, Silvio De Angelis, M. Carmen Benítez, Luciano Zuccarello, Richard G. Baraniuk, Jesús M. Ibáñez, Maarten V. de Hoop
2022	J	`jnl`	Retrieval-based Controllable Molecule Generation. CoRR Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar
2022	J	`jnl`	Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. SIAM J. Imaging Sci. Bao Wang, Tan M. Nguyen, Tao Sun, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2022	J	`jnl`	Singular Value Perturbation and Deep Network Optimization. CoRR Rudolf H. Riedi, Randall Balestriero, Richard G. Baraniuk
2022	—	`conf`	Spatial Transformer K-Means. IEEECONF Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
2022	J	`jnl`	Spatial Transformer K-Means. CoRR Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
2022	B	`conf`	Third Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Ben Motz, Debshila Basu Mallick, Klinton Bicknell, Danielle S. McNamara, René F. Kizilcec, Jeremy Roschelle, Richard G. Baraniuk, Ryan Baker
2022	—	`conf`	Towards Human-Like Educational Question Generation with Large Language Models. AIED (1) Zichao Wang, Jakob Valdez, Debshila Basu Mallick, Richard G. Baraniuk
2022	J	`jnl`	Uniform Partitioning of Data Grid for Association Detection. IEEE Trans. Pattern Anal. Mach. Intell. Ali Mousavi, Richard G. Baraniuk
2022	Misc	`conf`	Unrolling Particles: Unsupervised Learning of Sampling Distributions. ICASSP Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
2021	—	`conf`	A Case Study in Bootstrapping Ontology Graphs from Textbooks. AKBC Vinay K. Chaudhri, Matthew Boggess, Han Lin Aung, Debshila Basu Mallick, Andrew C. Waters, Richard G. Baraniuk
2021	J	`jnl`	A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning. CoRR Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk
2021	J	`jnl`	A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device. IEEE Trans. Haptics Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Indu Manickam, Gautam Dasarathy, Richard G. Baraniuk, Marcia K. O'Malley
2021	—	`conf`	A Relationship Selection Task (short paper). iTextbooks@AIED Andrew E. Waters, Vinay K. Chaudhri, Debshila Basu Mallick, Richard G. Baraniuk
2021	—	`conf`	Deep Autoencoders: From Understanding to Generalization Guarantees. MSML Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang
2021	J	`jnl`	Double Descent and Other Interpolation Phenomena in GANs. CoRR Lorenzo Luzi, Yehuda Dar, Richard G. Baraniuk
2021	A*	`conf`	Educational Question Mining At Scale: Prediction, Analysis and Personalization. AAAI Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang
2021	J	`jnl`	Evaluating generative networks using Gaussian mixtures of image features. CoRR Lorenzo Luzi, Carlos Ortiz Marrero, Nile Wynar, Richard G. Baraniuk, Michael J. Henry
2021	J	`jnl`	Fast Jacobian-Vector Product for Deep Networks. CoRR Randall Balestriero, Richard G. Baraniuk
2021	—	`conf`	Interpretable and Learnable Super-Resolution Time-Frequency Representation. MSML Randall Balestriero, Hervé Glotin, Richard G. Baraniuk
2021	J	`jnl`	MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. CoRR Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
2021	J	`jnl`	Mad Max: Affine Spline Insights Into Deep Learning. Proc. IEEE Randall Balestriero, Richard G. Baraniuk
2021	B	`conf`	Math Operation Embeddings for Open-ended Solution Analysis and Feedback. EDM Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2021	J	`jnl`	Math Operation Embeddings for Open-ended Solution Analysis and Feedback. CoRR Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2021	—	`conf`	Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. EMNLP (1) Zichao Wang, Andrew S. Lan, Richard G. Baraniuk
2021	J	`jnl`	Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. CoRR Zichao Wang, Andrew S. Lan, Richard G. Baraniuk
2021	—	`conf`	Mathematical Formula Representation via Tree Embeddings. iTextbooks@AIED Zichao Wang, Andrew S. Lan, Richard G. Baraniuk
2021	J	`jnl`	Max-Affine Spline Insights Into Deep Network Pruning. CoRR Randall Balestriero, Haoran You, Zhihan Lu, Yutong Kou, Yingyan Lin, Richard G. Baraniuk
2021	—	`conf`	Minipatch Learning as Implicit Ridge-Like Regularization. BigComp Tianyi Yao, Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk, Genevera I. Allen
2021	J	`jnl`	NFT-K: Non-Fungible Tangent Kernels. CoRR Sina Alemohammad, Hossein Babaei, C. J. Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk
2021	J	`jnl`	NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion. CoRR Shashank Sonkar, Arzoo Katiyar, Richard G. Baraniuk
2021	—	`conf`	NePTuNe: Neural Powered Tucker Networkfor Knowledge Graph Completion. IJCKG Shashank Sonkar, Arzoo Katiyar, Richard G. Baraniuk
2021	J	`jnl`	NeuroView: Explainable Deep Network Decision Making. CoRR C. J. Barberan, Randall Balestriero, Richard G. Baraniuk
2021	—	`ed.`	Proceedings of the Third International Workshop on Inteligent Textbooks 2021 Co-located with 22nd International Conference on Artificial Intelligence in Education (AIED 2021), Online, June 15, 2021. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Andrew S. Lan
2021	J	`jnl`	Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge. CoRR Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang
2021	J	`jnl`	SASSI - Super-Pixelated Adaptive Spatio-Spectral Imaging. IEEE Trans. Pattern Anal. Mach. Intell. Vishwanath Saragadam, Michael DeZeeuw, Richard G. Baraniuk, Ashok Veeraraghavan, Aswin C. Sankaranarayanan
2021	—	`conf`	Scientific Formula Retrieval via Tree Embeddings. IEEE BigData Zichao Wang, Mengxue Zhang, Richard G. Baraniuk, Andrew S. Lan
2021	A*	`conf`	The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. NeurIPS Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk
2021	J	`jnl`	The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. CoRR Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk
2021	A*	`conf`	The Recurrent Neural Tangent Kernel. ICLR Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard G. Baraniuk
2021	—	`conf`	Thermal Image Processing via Physics-Inspired Deep Networks. ICCVW Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan, Richard G. Baraniuk
2021	J	`jnl`	Thermal Image Processing via Physics-Inspired Deep Networks. CoRR Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan, Richard G. Baraniuk
2021	—	`conf`	Towards Blooms Taxonomy Classification Without Labels. AIED (1) Zichao Wang, Kyle Manning, Debshila Basu Mallick, Richard G. Baraniuk
2021	J	`jnl`	Transfer Learning Can Outperform the True Prior in Double Descent Regularization. CoRR Yehuda Dar, Richard G. Baraniuk
2021	J	`jnl`	Transformer with a Mixture of Gaussian Keys. CoRR Tam Nguyen, Tan M. Nguyen, Dung Le, Khuong Nguyen, Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
2021	J	`jnl`	Unrolling Particles: Unsupervised Learning of Sampling Distributions. CoRR Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
2021	Misc	`conf`	Wearing A Mask: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. ICASSP Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk
2020	J	`jnl`	An Improved Semi-Supervised VAE for Learning Disentangled Representations. CoRR Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk
2020	J	`jnl`	Analytical Probability Distributions and EM-Learning for Deep Generative Networks. CoRR Randall Balestriero, Sébastien Paris, Richard G. Baraniuk
2020	A*	`conf`	Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks. NeurIPS Randall Balestriero, Sébastien Paris, Richard G. Baraniuk
2020	B	`conf`	Attention Word Embedding. COLING Shashank Sonkar, Andrew E. Waters, Richard G. Baraniuk
2020	J	`jnl`	Attention Word Embedding. CoRR Shashank Sonkar, Andrew E. Waters, Richard G. Baraniuk
2020	A	`conf`	CANOPIC: Pre-Digital Privacy-Enhancing Encodings for Computer Vision. ICME Jasper Tan, Salman Siddique Khan, Vivek Boominathan, Jeffrey Byrne, Richard G. Baraniuk, Kaushik Mitra, Ashok Veeraraghavan
2020	J	`jnl`	Computer-Aided Personalized Education. CoRR Rajeev Alur, Richard G. Baraniuk, Rastislav Bodík, Ann W. Drobnis, Sumit Gulwani, Bjoern Hartmann, Yasmin B. Kafai, Jeff Karpicke, Ran Libeskind-Hadas, Debra J. Richardson, Armando Solar-Lezama, Candace Thille, Moshe Y. Vardi
2020	J	`jnl`	Deep Learning Techniques for Inverse Problems in Imaging. CoRR Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett
2020	J	`jnl`	Deep Learning Techniques for Inverse Problems in Imaging. IEEE J. Sel. Areas Inf. Theory Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett
2020	J	`jnl`	Diagnostic Questions: The NeurIPS 2020 Education Challenge. CoRR Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang
2020	J	`jnl`	Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. CoRR Yehuda Dar, Richard G. Baraniuk
2020	A*	`conf`	Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. ICLR Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin
2020	J	`jnl`	Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference. IEEE J. Sel. Top. Signal Process. Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin
2020	J	`jnl`	Ensembles of Generative Adversarial Networks for Disconnected Data. CoRR Lorenzo Luzi, Randall Balestriero, Richard G. Baraniuk
2020	J	`jnl`	Guest Editorial. IEEE J. Sel. Areas Inf. Theory Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett
2020	—	`conf`	Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform. iTextbooks@AIED David Y. J. Kim, Adam Winchell, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk, Michael Mozer
2020	J	`jnl`	Interpretable Image Clustering via Diffeomorphism-Aware K-Means. CoRR Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
2020	J	`jnl`	Interpretable Super-Resolution via a Learned Time-Series Representation. CoRR Randall Balestriero, Hervé Glotin, Richard G. Baraniuk
2020	J	`jnl`	Inverse Scattering via Transmission Matrices: Broadband Illumination and Fast Phase Retrieval Algorithms. IEEE Trans. Computational Imaging Manoj Kumar Sharma, Christopher A. Metzler, Sudarshan Nagesh, Richard G. Baraniuk, Oliver Cossairt, Ashok Veeraraghavan
2020	J	`jnl`	Max-Affine Spline Insights into Deep Generative Networks. CoRR Randall Balestriero, Sébastien Paris, Richard G. Baraniuk
2020	A*	`conf`	MomentumRNN: Integrating Momentum into Recurrent Neural Networks. NeurIPS Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2020	J	`jnl`	MomentumRNN: Integrating Momentum into Recurrent Neural Networks. CoRR Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2020	—	`ed.`	Proceedings of the Second International Workshop on Intelligent Textbooks 2020 co-located with 21st International Conference on Artificial Intelligence in Education (AIED 2020), Online, July 06, 2020. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Andrew S. Lan
2020	J	`jnl`	Provable Finite Data Generalization with Group Autoencoder. CoRR Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang
2020	—	`conf`	Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge. NeurIPS (Competition and Demos) Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang
2020	J	`jnl`	SASSI - Super-Pixelated Adaptive Spatio-Spectral Imaging. CoRR Vishwanath Saragadam, Michael DeZeeuw, Richard G. Baraniuk, Ashok Veeraraghavan, Aswin C. Sankaranarayanan
2020	J	`jnl`	Scalable Neural Tangent Kernel of Recurrent Architectures. CoRR Sina Alemohammad, Randall Balestriero, Zichao Wang, Richard G. Baraniuk
2020	J	`jnl`	Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. CoRR Bao Wang, Tan M. Nguyen, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2020	A*	`conf`	Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. ICML Benjamin Coleman, Richard G. Baraniuk, Anshumali Shrivastava
2020	A*	`conf`	Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. ICML Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk
2020	J	`jnl`	Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. CoRR Yehuda Dar, Paul M. Mayer, Lorenzo Luzi, Richard G. Baraniuk
2020	A	`conf`	The Implicit Regularization of Ordinary Least Squares Ensembles. AISTATS Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk
2020	J	`jnl`	The Recurrent Neural Tangent Kernel. CoRR Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard G. Baraniuk
2020	J	`jnl`	The science of deep learning. Proc. Natl. Acad. Sci. USA Richard G. Baraniuk, David L. Donoho, Matan Gavish
2020	A	`conf`	Thresholding Graph Bandits with GrAPL. AISTATS Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk
2020	J	`jnl`	Universal Frame Thresholding. IEEE Signal Process. Lett. Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang
2020	B	`conf`	VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. EDM Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk
2020	J	`jnl`	VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. CoRR Jack Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk
2020	J	`jnl`	Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. CoRR Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk
2020	B	`conf`	qDKT: Question-centric Deep Knowledge Tracing. EDM Shashank Sonkar, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk
2020	J	`jnl`	qDKT: Question-centric Deep Knowledge Tracing. CoRR Shashank Sonkar, Andrew E. Waters, Andrew S. Lan, Phillip J. Grimaldi, Richard G. Baraniuk
2019	—	`conf`	A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery. ICLR (Poster) Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
2019	J	`jnl`	A Hessian Based Complexity Measure for Deep Networks. CoRR Hamid Javadi, Randall Balestriero, Richard G. Baraniuk
2019	—	`conf`	A Max-Affine Spline Perspective of Recurrent Neural Networks. ICLR (Poster) Zichao Wang, Randall Balestriero, Richard G. Baraniuk
2019	B	`conf`	A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading. EDM Zichao Wang, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk
2019	A	`conf`	Adaptive Estimation for Approximate AISTATS Daniel LeJeune, Reinhard Heckel, Richard G. Baraniuk
2019	J	`jnl`	Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. CoRR Daniel LeJeune, Richard G. Baraniuk, Reinhard Heckel
2019	J	`jnl`	Drawing early-bird tickets: Towards more efficient training of deep networks. CoRR Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk
2019	J	`jnl`	Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference. CoRR Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin
2019	J	`jnl`	Face Detection and Verification Using Lensless Cameras. IEEE Trans. Computational Imaging Jasper Tan, Li Niu, Jesse K. Adams, Vivek Boominathan, Jacob T. Robinson, Richard G. Baraniuk, Ashok Veeraraghavan
2019	—	`conf`	From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. ICLR (Poster) Randall Balestriero, Richard G. Baraniuk
2019	J	`jnl`	IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election. CoRR Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk
2019	B	`conf`	IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. ASONAM Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk
2019	J	`jnl`	InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers. CoRR Tan M. Nguyen, Animesh Garg, Richard G. Baraniuk, Anima Anandkumar
2019	J	`jnl`	Out-of-Distribution Detection Using Neural Rendering Generative Models. CoRR Yujia Huang, Sihui Dai, Tan M. Nguyen, Richard G. Baraniuk, Anima Anandkumar
2019	—	`ed.`	Proceedings of the First Workshop on Intelligent Textbooks co-located with 20th International Conference on Artificial Intelligence in Education (AIED 2019), Chicago, IL, USA, June 25, 2019. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Rakesh Agrawal, Andrew S. Lan
2019	J	`jnl`	RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. CoRR Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk
2019	—	`conf`	Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. ICLR (Poster) Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel
2019	J	`jnl`	Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. CoRR Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel
2019	A*	`conf`	The Geometry of Deep Networks: Power Diagram Subdivision. NeurIPS Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk
2019	J	`jnl`	The Geometry of Deep Networks: Power Diagram Subdivision. CoRR Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk
2019	J	`jnl`	The Implicit Regularization of Ordinary Least Squares Ensembles. CoRR Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk
2019	J	`jnl`	Thresholding Graph Bandits with GrAPL. CoRR Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk
2018	J	`jnl`	A Spline Theory of Deep Networks (Extended Version). CoRR Randall Balestriero, Richard G. Baraniuk
2018	A*	`conf`	A Spline Theory of Deep Networks. ICML Randall Balestriero, Richard G. Baraniuk
2018	—	`conf`	An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing. LVA/ICA Christopher A. Metzler, Philip Schniter, Richard G. Baraniuk
2018	J	`jnl`	An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing. CoRR Christopher A. Metzler, Philip Schniter, Richard G. Baraniuk
2018	Misc	`conf`	Conveying language through haptics: a multi-sensory approach. UbiComp Nathan Dunkelberger, Jennifer L. Sullivan, Joshua Bradley, Nickolas P. Walling, Indu Manickam, Gautam Dasarathy, Ali Israr, Frances W. Y. Lau, Keith Klumb, Brian Knott, Freddy Abnousi, Richard G. Baraniuk, Marcia K. O'Malley
2018	J	`jnl`	From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. CoRR Randall Balestriero, Richard G. Baraniuk
2018	Misc	`conf`	Insense: Incoherent Sensor Selection for Sparse Signals. ICASSP Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk
2018	J	`jnl`	Insense: Incoherent sensor selection for sparse signals. Signal Process. Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk
2018	A*	`conf`	MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. ICML Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
2018	J	`jnl`	MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. CoRR Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, Richard G. Baraniuk
2018	J	`jnl`	Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning. CoRR Nhat Ho, Tan M. Nguyen, Ankit B. Patel, Anima Anandkumar, Michael I. Jordan, Richard G. Baraniuk
2018	B	`conf`	QG-net: a data-driven question generation model for educational content. L@S Zichao Wang, Andrew S. Lan, Weili Nie, Andrew E. Waters, Phillip J. Grimaldi, Richard G. Baraniuk
2018	J	`jnl`	RankMap: A Framework for Distributed Learning From Dense Data Sets. IEEE Trans. Neural Networks Learn. Syst. Azalia Mirhoseini, Eva L. Dyer, Ebrahim M. Songhori, Richard G. Baraniuk, Farinaz Koushanfar
2018	J	`jnl`	Semi-Supervised Learning Enabled by Multiscale Deep Neural Network Inversion. CoRR Randall Balestriero, Hervé Glotin, Richard G. Baraniuk
2018	A*	`conf`	Spline Filters For End-to-End Deep Learning. ICML Randall Balestriero, Romain Cosentino, Hervé Glotin, Richard G. Baraniuk
2018	J	`jnl`	Unsupervised Learning with Stein's Unbiased Risk Estimator. CoRR Christopher A. Metzler, Ali Mousavi, Reinhard Heckel, Richard G. Baraniuk
2018	J	`jnl`	prDeep: Robust Phase Retrieval with Flexible Deep Neural Networks. CoRR Christopher A. Metzler, Philip Schniter, Ashok Veeraraghavan, Richard G. Baraniuk
2018	A*	`conf`	prDeep: Robust Phase Retrieval with a Flexible Deep Network. ICML Christopher A. Metzler, Philip Schniter, Ashok Veeraraghavan, Richard G. Baraniuk
2017	B	`conf`	A Latent Factor Model For Instructor Content Preference Analysis. EDM Jack Z. Wang, Andrew S. Lan, Phillip Grimaldi, Richard G. Baraniuk
2017	J	`jnl`	Adaptive Partitioning Spline Neural Networks: Template Matching, Memorization, Inhibitor Connections, Inversion, Semi-Sup, Topology Search. CoRR Randall Balestriero, Richard G. Baraniuk
2017	J	`jnl`	BLAh: Boolean Logic Analysis for Graded Student Response Data. IEEE J. Sel. Top. Signal Process. Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2017	B	`conf`	Coherent inverse scattering via transmission matrices: Efficient phase retrieval algorithms and a public dataset. ICCP Christopher A. Metzler, Manoj Kumar Sharma, Sudarshan Nagesh, Richard G. Baraniuk, Oliver Cossairt, Ashok Veeraraghavan
2017	J	`jnl`	Compressive Video Sensing: Algorithms, architectures, and applications. IEEE Signal Process. Mag. Richard G. Baraniuk, Thomas A. Goldstein, Aswin C. Sankaranarayanan, Christoph Studer, Ashok Veeraraghavan, Michael B. Wakin
2017	Misc	`conf`	Contextual multi-armed bandit algorithms for personalized learning action selection. ICASSP Indu Manickam, Andrew S. Lan, Richard G. Baraniuk
2017	B	`conf`	D.TRUMP: Data-mining Textual Responses to Uncover Misconception Patterns. L@S Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk
2017	B	`conf`	Data-Mining Textual Responses to Uncover Misconception Patterns. EDM Joshua J. Michalenko, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk
2017	J	`jnl`	Data-Mining Textual Responses to Uncover Misconception Patterns. CoRR Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk
2017	J	`jnl`	DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks. CoRR Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
2017	—	`conf`	DeepCodec: Adaptive sensing and recovery via deep convolutional neural networks. Allerton Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
2017	J	`jnl`	Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals. IEEE Trans. Inf. Theory Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters
2017	Misc	`conf`	Flat focus: depth of field analysis for the FlatCam lensless imaging system. ICASSP Jasper Tan, Vivek Boominathan, Ashok Veeraraghavan, Richard G. Baraniuk
2017	J	`jnl`	FlatCam: Thin, Lensless Cameras Using Coded Aperture and Computation. IEEE Trans. Computational Imaging M. Salman Asif, Ali Ayremlou, Aswin C. Sankaranarayanan, Ashok Veeraraghavan, Richard G. Baraniuk
2017	J	`jnl`	Insense: Incoherent Sensor Selection for Sparse Signals. CoRR Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk
2017	J	`jnl`	Introduction to the Issue on Signal Processing and Machine Learning. IEEE J. Sel. Top. Signal Process. Mihaela van der Schaar, Richard G. Baraniuk, Mung Chiang, Jonathan Huang, Shengdong Zhao
2017	J	`jnl`	Learned D-AMP: A Principled CNN-based Compressive Image Recovery Algorithm. CoRR Christopher A. Metzler, Ali Mousavi, Richard G. Baraniuk
2017	—	`conf`	Learned D-AMP: Principled Neural Network based Compressive Image Recovery. NIPS Christopher A. Metzler, Ali Mousavi, Richard G. Baraniuk
2017	J	`jnl`	Learning to Invert: Signal Recovery via Deep Convolutional Networks. CoRR Ali Mousavi, Richard G. Baraniuk
2017	Misc	`conf`	Learning to invert: Signal recovery via Deep Convolutional Networks. ICASSP Ali Mousavi, Richard G. Baraniuk
2017	J	`jnl`	Overcomplete Frame Thresholding for Acoustic Scene Analysis. CoRR Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Ankit B. Patel
2017	B	`conf`	Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks. EDM Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk
2017	A*	`conf`	RHash: Robust Hashing via L_infinity-norm Distortion. IJCAI Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk
2017	J	`jnl`	Semi-Supervised Learning via New Deep Network Inversion. CoRR Randall Balestriero, Vincent Roger, Hervé Glotin, Richard G. Baraniuk
2017	B	`conf`	Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning. EDM Andrew E. Waters, Phillip Grimaldi, Andrew S. Lan, Richard G. Baraniuk
2017	Misc	`conf`	Sketched covariance testing: A compression-statistics tradeoff. ACSSC Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk
2017	B	`conf`	Sketched covariance testing: A compression-statistics tradeoff. ISIT Gautam Dasarathy, Parikshit Shah, Richard G. Baraniuk
2016	B	`conf`	A Contextual Bandits Framework for Personalized Learning Action Selection. EDM Andrew S. Lan, Richard G. Baraniuk
2016	—	`conf`	A Probabilistic Framework for Deep Learning. NIPS Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk
2016	J	`jnl`	A Probabilistic Framework for Deep Learning. CoRR Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk
2016	B	`conf`	BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising. ICIP Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk
2016	—	`conf`	BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising. ICME Workshops Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk
2016	A*	`conf`	Dealbreaker: A Nonlinear Latent Variable Model for Educational Data. ICML Andrew S. Lan, Tom Goldstein, Richard G. Baraniuk, Christoph Studer
2016	A	`conf`	Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition. SDM Raajen Patel, Tom Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk
2016	J	`jnl`	From Denoising to Compressed Sensing. IEEE Trans. Inf. Theory Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk
2016	J	`jnl`	Lensless Imaging: A computational renaissance. IEEE Signal Process. Mag. Vivek Boominathan, Jesse K. Adams, M. Salman Asif, Benjamin W. Avants, Jacob T. Robinson, Richard G. Baraniuk, Aswin C. Sankaranarayanan, Ashok Veeraraghavan
2016	J	`jnl`	MOOC Adventures in Signal Processing: Bringing DSP to the era of massive open online courses. IEEE Signal Process. Mag. Thomas A. Baran, Richard G. Baraniuk, Alan V. Oppenheim, Paolo Prandoni, Martin Vetterli
2016	J	`jnl`	Near-Isometric Binary Hashing for Large-scale Datasets. CoRR Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk
2016	J	`jnl`	One-Bit Compressive Sensing of Dictionary-Sparse Signals. CoRR Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters
2016	—	`conf`	Optimal ranking of test items using the Rasch model. Allerton Divyanshu Vats, Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2016	J	`jnl`	Semi-Supervised Learning with the Deep Rendering Mixture Model. CoRR Minh Tan Nguyen, Wanjia Liu, Ethan Perez, Richard G. Baraniuk, Ankit B. Patel
2016	J	`jnl`	Signal Processing for Computational Photography and Displays [From the Guest Editors]. IEEE Signal Process. Mag. Amit K. Agrawal, Richard G. Baraniuk, Pablo Favaro, Ashok Veeraraghavan
2015	J	`jnl`	A Deep Learning Approach to Structured Signal Recovery. CoRR Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk
2015	J	`jnl`	A Probabilistic Theory of Deep Learning. CoRR Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk
2015	—	`conf`	A deep learning approach to structured signal recovery. Allerton Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk
2015	J	`jnl`	An Information-Theoretic Measure of Dependency Among Variables in Large Datasets. CoRR Ali Mousavi, Richard G. Baraniuk
2015	—	`conf`	An information-theoretic measure of dependency among variables in large datasets. Allerton Ali Mousavi, Richard G. Baraniuk
2015	B	`conf`	BM3D-AMP: A new image recovery algorithm based on BM3D denoising. ICIP Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk
2015	B	`conf`	BayesRank: A Bayesian Approach to Ranked Peer Grading. L@S Andrew E. Waters, David Tinapple, Richard G. Baraniuk
2015	J	`jnl`	Consistent Parameter Estimation for LASSO and Approximate Message Passing. CoRR Ali Mousavi, Arian Maleki, Richard G. Baraniuk
2015	—	`conf`	Dynamic model generation for application of compressed sensing to cryo-electron tomography reconstruction. SP/SPE Sally L. Wood, Ernesto Fontenla, Christopher A. Metzler, Wah Chiu, Richard G. Baraniuk
2015	J	`jnl`	FASTA: A Generalized Implementation of Forward-Backward Splitting. CoRR Tom Goldstein, Christoph Studer, Richard G. Baraniuk
2015	—	`conf`	FlatCam: Replacing Lenses with Masks and Computation. ICCV Workshops M. Salman Asif, Ali Ayremlou, Ashok Veeraraghavan, Richard G. Baraniuk, Aswin C. Sankaranarayanan
2015	J	`jnl`	FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation. CoRR M. Salman Asif, Ali Ayremlou, Aswin C. Sankaranarayanan, Ashok Veeraraghavan, Richard G. Baraniuk
2015	Misc	`conf`	Iterative reconstruction from limited angle, limited view projections for cryo-electron tomography. ACSSC Sally L. Wood, Ernesto Fontenla, Christopher A. Metzler, Wah Chiu, Richard G. Baraniuk
2015	B	`conf`	Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. L@S Andrew S. Lan, Divyanshu Vats, Andrew E. Waters, Richard G. Baraniuk
2015	J	`jnl`	Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. CoRR Andrew S. Lan, Divyanshu Vats, Andrew E. Waters, Richard G. Baraniuk
2015	J	`jnl`	NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings. IEEE Trans. Signal Process. Chinmay Hegde, Aswin C. Sankaranarayanan, Wotao Yin, Richard G. Baraniuk
2015	J	`jnl`	RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets. CoRR Azalia Mirhoseini, Eva L. Dyer, Ebrahim M. Songhori, Richard G. Baraniuk, Farinaz Koushanfar
2015	J	`jnl`	Self-Expressive Decompositions for Matrix Approximation and Clustering. CoRR Eva L. Dyer, Tom Goldstein, Raajen Patel, Konrad P. Körding, Richard G. Baraniuk
2015	J	`jnl`	The STOne Transform: Multi-Resolution Image Enhancement and Compressive Video. IEEE Trans. Image Process. Tom Goldstein, Lina Xu, Kevin F. Kelly, Richard G. Baraniuk
2015	J	`jnl`	Video Compressive Sensing for Spatial Multiplexing Cameras Using Motion-Flow Models. SIAM J. Imaging Sci. Aswin C. Sankaranarayanan, Lina Xu, Christoph Studer, Yun Li, Kevin F. Kelly, Richard G. Baraniuk
2015	J	`jnl`	Video Compressive Sensing for Spatial Multiplexing Cameras using Motion-Flow Models. CoRR Aswin C. Sankaranarayanan, Lina Xu, Christoph Studer, Yun Li, Kevin F. Kelly, Richard G. Baraniuk
2015	J	`jnl`	oASIS: Adaptive Column Sampling for Kernel Matrix Approximation. CoRR Raajen Patel, Thomas A. Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk
2014	J	`jnl`	A Field Guide to Forward-Backward Splitting with a FASTA Implementation. CoRR Tom Goldstein, Christoph Studer, Richard G. Baraniuk
2014	A	`conf`	Active Learning for Undirected Graphical Model Selection. AISTATS Divyanshu Vats, Robert D. Nowak, Richard G. Baraniuk
2014	J	`jnl`	Active Learning for Undirected Graphical Model Selection. CoRR Divyanshu Vats, Robert D. Nowak, Richard G. Baraniuk
2014	—	`ch.`	Compressive Sensing. Computer Vision, A Reference Guide Aswin C. Sankaranarayanan, Richard G. Baraniuk
2014	J	`jnl`	Democratic Representations. CoRR Christoph Studer, Tom Goldstein, Wotao Yin, Richard G. Baraniuk
2014	J	`jnl`	Exponential decay of reconstruction error from binary measurements of sparse signals. CoRR Richard G. Baraniuk, Simon Foucart, Deanna Needell, Yaniv Plan, Mary Wootters
2014	J	`jnl`	Fast Alternating Direction Optimization Methods. SIAM J. Imaging Sci. Tom Goldstein, Brendan O'Donoghue, Simon Setzer, Richard G. Baraniuk
2014	J	`jnl`	Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit. CoRR Ali Ayremlou, Thomas A. Goldstein, Ashok Veeraraghavan, Richard G. Baraniuk
2014	J	`jnl`	From Denoising to Compressed Sensing. CoRR Christopher A. Metzler, Arian Maleki, Richard G. Baraniuk
2014	Misc	`conf`	LIE operators for compressive sensing. ICASSP Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2014	Misc	`conf`	Matrix recovery from quantized and corrupted measurements. ICASSP Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Minimum Complexity Pursuit for Universal Compressed Sensing. IEEE Trans. Inf. Theory Shirin Jalali, Arian Maleki, Richard G. Baraniuk
2014	A	`conf`	Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression. AISTATS Divyanshu Vats, Richard G. Baraniuk
2014	J	`jnl`	Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression. CoRR Divyanshu Vats, Richard G. Baraniuk
2014	B	`conf`	Quantized Matrix Completion for Personalized Learning. EDM Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Quantized Matrix Completion for Personalized Learning. CoRR Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Sparse Bilinear Logistic Regression. CoRR Jianing Shi, Yangyang Xu, Richard G. Baraniuk
2014	J	`jnl`	Sparse factor analysis for learning and content analytics. J. Mach. Learn. Res. Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection. IEEE Signal Process. Mag. Rebecca M. Willett, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk
2014	J	`jnl`	Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. CoRR Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2014	A*	`conf`	Time-varying learning and content analytics via sparse factor analysis. KDD Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Toward Compressive Camera Networks. Computer Kaushik Mitra, Ashok Veeraraghavan, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2014	J	`jnl`	Video Compressive Sensing for Dynamic MRI. CoRR Jianing Shi, Wotao Yin, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2013	Misc	`conf`	Adaptive step size selection for optimization via the ski rental problem. ICASSP Amirali Aghazadeh, Ali Ayremlou, Daniel D. Calderon, Tom Goldstein, Raajen Patel, Divyanshu Vats, Richard G. Baraniuk
2013	J	`jnl`	Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP). IEEE Trans. Inf. Theory Arian Maleki, Laura Anitori, Zai Yang, Richard G. Baraniuk
2013	J	`jnl`	Asymptotic Analysis of LASSOs Solution Path with Implications for Approximate Message Passing. CoRR Ali Mousavi, Arian Maleki, Richard G. Baraniuk
2013	—	`conf`	Bayesian pairwise collaboration detection in educational datasets. GlobalSIP Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2013	J	`jnl`	Compressive Acquisition of Linear Dynamical Systems. SIAM J. Imaging Sci. Aswin C. Sankaranarayanan, Pavan K. Turaga, Rama Chellappa, Richard G. Baraniuk
2013	—	`conf`	Compressive sensing radar: Simulation and experiments for target detection. EUSIPCO Laura Anitori, Wim Van Rossum, Matern Otten, Arian Maleki, Richard G. Baraniuk
2013	J	`jnl`	Design and Analysis of Compressed Sensing Radar Detectors. IEEE Trans. Signal Process. Laura Anitori, Arian Maleki, Matern Otten, Richard G. Baraniuk, Peter Hoogeboom
2013	J	`jnl`	Greedy Feature Selection for Subspace Clustering CoRR Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2013	J	`jnl`	Greedy feature selection for subspace clustering. J. Mach. Learn. Res. Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2013	J	`jnl`	Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data CoRR Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2013	B	`conf`	Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data. EDM Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2013	J	`jnl`	Maximin Analysis of Message Passing Algorithms for Recovering Block Sparse Signals CoRR Armeen Taeb, Arian Maleki, Christoph Studer, Richard G. Baraniuk
2013	J	`jnl`	Measurement Bounds for Sparse Signal Ensembles via Graphical Models. IEEE Trans. Inf. Theory Marco F. Duarte, Michael B. Wakin, Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
2013	Misc	`conf`	Open online platforms advancing DSP education. ICASSP John P. Slavinsky, Kim J. Davenport, Andrew C. Butler, Elizabeth J. Marsh, Richard G. Baraniuk
2013	J	`jnl`	Parameterless Optimal Approximate Message Passing. CoRR Ali Mousavi, Arian Maleki, Richard G. Baraniuk
2013	J	`jnl`	Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors. IEEE Trans. Inf. Theory Laurent Jacques, Jason N. Laska, Petros T. Boufounos, Richard G. Baraniuk
2013	J	`jnl`	Sparse Factor Analysis for Learning and Content Analytics CoRR Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2013	Misc	`conf`	Subspace clustering with dense representations. ICASSP Eva L. Dyer, Christoph Studer, Richard G. Baraniuk
2013	J	`jnl`	Swapping Variables for High-Dimensional Sparse Regression from Correlated Measurements. CoRR Divyanshu Vats, Richard G. Baraniuk
2013	B	`conf`	Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. EDM Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2013	B	`conf`	Test-size Reduction for Concept Estimation. EDM Divyanshu Vats, Christoph Studer, Andrew S. Lan, Lawrence Carin, Richard G. Baraniuk
2013	J	`jnl`	The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video. CoRR Tom Goldstein, Lina Xu, Kevin F. Kelly, Richard G. Baraniuk
2013	J	`jnl`	Time-varying Learning and Content Analytics via Sparse Factor Analysis. CoRR Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2013	—	`conf`	When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements. NIPS Divyanshu Vats, Richard G. Baraniuk
2012	Misc	`conf`	A bit-constrained sar adc for compressive acquisition of frequency sparse signals. ICASSP Andrew E. Waters, Charles K. Sestok, Richard G. Baraniuk
2012	Misc	`conf`	A compressive phase-locked loop. ICASSP Stephen R. Schnelle, John P. Slavinsky, Petros Boufounos, Mark A. Davenport, Richard G. Baraniuk
2012	B	`conf`	CS-MUVI: Video compressive sensing for spatial-multiplexing cameras. ICCP Aswin C. Sankaranarayanan, Christoph Studer, Richard G. Baraniuk
2012	J	`jnl`	Compressive Acquisition of Dynamic Scenes CoRR Aswin C. Sankaranarayanan, Pavan K. Turaga, Rama Chellappa, Richard G. Baraniuk
2012	Misc	`conf`	Dictionary learning from sparsely corrupted or compressed signals. ICASSP Christoph Studer, Richard G. Baraniuk
2012	J	`jnl`	Kronecker Compressive Sensing. IEEE Trans. Image Process. Marco F. Duarte, Richard G. Baraniuk
2012	J	`jnl`	Minimum Complexity Pursuit for Universal Compressed Sensing CoRR Shirin Jalali, Arian Maleki, Richard G. Baraniuk
2012	J	`jnl`	Minimum Complexity Pursuit: Stability Analysis CoRR Shirin Jalali, Arian Maleki, Richard G. Baraniuk
2012	B	`conf`	Minimum complexity pursuit: Stability analysis. ISIT Shirin Jalali, Arian Maleki, Richard G. Baraniuk
2012	—	`conf`	Multi-objective sensor-based replanning for a car-like robot. SSRR Devin K. Grady, Mark Moll, Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk, Lydia E. Kavraki
2012	—	`conf`	Multi-robot target verification with reachability constraints. SSRR Devin K. Grady, Mark Moll, Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk, Lydia E. Kavraki
2012	—	`conf`	Near-isometric linear embeddings of manifolds. SSP Chinmay Hegde, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2012	J	`jnl`	Regime Change: Bit-Depth Versus Measurement-Rate in Compressive Sensing. IEEE Trans. Signal Process. Jason N. Laska, Richard G. Baraniuk
2012	B	`conf`	SPIN: Iterative signal recovery on incoherent manifolds. ISIT Chinmay Hegde, Richard G. Baraniuk
2012	—	`conf`	Sequentially designed compressed sensing. SSP Jarvis D. Haupt, Richard G. Baraniuk, Rui M. Castro, Robert D. Nowak
2012	J	`jnl`	Signal Recovery on Incoherent Manifolds CoRR Chinmay Hegde, Richard G. Baraniuk
2012	J	`jnl`	Signal Recovery on Incoherent Manifolds. IEEE Trans. Inf. Theory Chinmay Hegde, Richard G. Baraniuk
2012	—	`conf`	Signal representations with minimum ℓ∞-norm. Allerton Conference Christoph Studer, Wotao Yin, Richard G. Baraniuk
2012	J	`jnl`	The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range. IEEE Trans. Signal Process. Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk
2012	J	`jnl`	Trends in Signal Processing Education [In the Spotlight]. IEEE Signal Process. Mag. Richard G. Baraniuk, Wayne T. Padgett
2012	J	`jnl`	VLSI Design of Approximate Message Passing for Signal Restoration and Compressive Sensing. IEEE J. Emerg. Sel. Topics Circuits Syst. Patrick Maechler, Christoph Studer, David E. Bellasi, Arian Maleki, Andreas Burg, Norbert Felber, Hubert Kaeslin, Richard G. Baraniuk
2011	J	`jnl`	A Theory for Optical flow-based Transport on Image Manifolds CoRR Sriram Nagaraj, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2011	J	`jnl`	Anisotropic Nonlocal Means Denoising CoRR Arian Maleki, Manjari Narayan, Richard G. Baraniuk
2011	J	`jnl`	Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP) CoRR Arian Maleki, Laura Anitori, Zai Yang, Richard G. Baraniuk
2011	J	`jnl`	Bounds on the Reconstruction of Sparse Signal Ensembles from Distributed Measurements CoRR Marco F. Duarte, Michael B. Wakin, Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
2011	J	`jnl`	Deterministic Bounds for Restricted Isometry of Compressed Sensing Matrices CoRR Shriram Sarvotham, Richard G. Baraniuk
2011	—	`conf`	Go with the flow: Optical flow-based transport operators for image manifolds. Allerton Aswin C. Sankaranarayanan, Chinmay Hegde, Sriram Nagaraj, Richard G. Baraniuk
2011	J	`jnl`	Learning Low-Dimensional Signal Models. IEEE Signal Process. Mag. Lawrence Carin, Richard G. Baraniuk, Volkan Cevher, David B. Dunson, Michael I. Jordan, Guillermo Sapiro, Michael B. Wakin
2011	B	`conf`	Least favorable compressed sensing problems for first-order methods. ISIT Arian Maleki, Richard G. Baraniuk
2011	—	`conf`	Recovery guarantees for restoration and separation of approximately sparse signals. Allerton Christoph Studer, Richard G. Baraniuk
2011	J	`jnl`	Regime Change: Bit-Depth versus Measurement-Rate in Compressive Sensing CoRR Jason N. Laska, Richard G. Baraniuk
2011	J	`jnl`	Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors CoRR Laurent Jacques, Jason N. Laska, Petros Boufounos, Richard G. Baraniuk
2011	Misc	`conf`	Robust support recovery using sparse compressive sensing matrices. CISS Jarvis D. Haupt, Richard G. Baraniuk
2011	J	`jnl`	Sampling and Recovery of Pulse Streams. IEEE Trans. Signal Process. Chinmay Hegde, Richard G. Baraniuk
2011	—	`conf`	SpaRCS: Recovering low-rank and sparse matrices from compressive measurements. NIPS Andrew E. Waters, Aswin C. Sankaranarayanan, Richard G. Baraniuk
2011	J	`jnl`	Stable Restoration and Separation of Approximately Sparse Signals CoRR Christoph Studer, Richard G. Baraniuk
2011	J	`jnl`	Suboptimality of Nonlocal Means for Images with Sharp Edges CoRR Arian Maleki, Manjari Narayan, Richard G. Baraniuk
2011	—	`conf`	Suboptimality of nonlocal means on images with sharp edges. Allerton Arian Maleki, Manjari Narayan, Richard G. Baraniuk
2011	J	`jnl`	The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range CoRR Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk
2011	Misc	`conf`	The compressive multiplexer for multi-channel compressive sensing. ICASSP John P. Slavinsky, Jason N. Laska, Mark A. Davenport, Richard G. Baraniuk
2011	—	`conf`	The polyphase random demodulator for wideband compressive sensing. ACSCC Jason N. Laska, John P. Slavinsky, Richard G. Baraniuk
2011	J	`jnl`	Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements. IEEE Trans. Signal Process. Jason N. Laska, Zaiwen Wen, Wotao Yin, Richard G. Baraniuk
2010	J	`jnl`	Applications of Sparse Representation and Compressive Sensing. Proc. IEEE Richard G. Baraniuk, Emmanuel J. Candès, Michael Elad, Yi Ma
2010	J	`jnl`	Bayesian compressive sensing via belief propagation. IEEE Trans. Signal Process. Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
2010	J	`jnl`	Beyond Nyquist: efficient sampling of sparse bandlimited signals. IEEE Trans. Inf. Theory Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk
2010	—	`conf`	Compressive Acquisition of Dynamic Scenes. ECCV (1) Aswin C. Sankaranarayanan, Pavan K. Turaga, Richard G. Baraniuk, Rama Chellappa
2010	Misc	`conf`	Compressive sensing of a superposition of pulses. ICASSP Chinmay Hegde, Richard G. Baraniuk
2010	—	`conf`	High Dimensional Data Fusion via Joint Manifold Learning. AAAI Fall Symposium: Manifold Learning and Its Applications Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
2010	J	`jnl`	Introduction to the Issue on Compressive Sensing. IEEE J. Sel. Top. Signal Process. Rick Chartrand, Richard G. Baraniuk, Yonina C. Eldar, Mário A. T. Figueiredo, Jared Tanner
2010	J	`jnl`	Joint Manifolds for Data Fusion. IEEE Trans. Image Process. Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
2010	Misc	`conf`	Kronecker product matrices for compressive sensing. ICASSP Marco F. Duarte, Richard G. Baraniuk
2010	J	`jnl`	Low-Dimensional Models for Dimensionality Reduction and Signal Recovery: A Geometric Perspective. Proc. IEEE Richard G. Baraniuk, Volkan Cevher, Michael B. Wakin
2010	J	`jnl`	Model-based compressive sensing. IEEE Trans. Inf. Theory Richard G. Baraniuk, Volkan Cevher, Marco F. Duarte, Chinmay Hegde
2010	—	`conf`	Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation. LVA/ICA Eva L. Dyer, Marco F. Duarte, Don H. Johnson, Richard G. Baraniuk
2010	—	`conf`	Recovery of frequency-sparse signals from compressive measurements. Allerton Marco F. Duarte, Richard G. Baraniuk
2010	J	`jnl`	Sampling and Recovery of Pulse Streams CoRR Chinmay Hegde, Richard G. Baraniuk
2010	J	`jnl`	Signal Processing With Compressive Measurements. IEEE J. Sel. Top. Signal Process. Mark A. Davenport, Petros Boufounos, Michael B. Wakin, Richard G. Baraniuk
2010	J	`jnl`	Sparse Signal Recovery and Acquisition with Graphical Models. IEEE Signal Process. Mag. Volkan Cevher, Piotr Indyk, Lawrence Carin, Richard G. Baraniuk
2010	Misc	`conf`	Texas Hold 'Em algorithms for distributed compressive sensing. ICASSP Stephen R. Schnelle, Jason N. Laska, Chinmay Hegde, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk
2010	J	`jnl`	Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification. IEEE Trans. Pattern Anal. Mach. Intell. Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
2009	J	`jnl`	A Theoretical Analysis of Joint Manifolds CoRR Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
2009	J	`jnl`	A simple proof that random matrices are democratic CoRR Mark A. Davenport, Jason N. Laska, Petros Boufounos, Richard G. Baraniuk
2009	J	`jnl`	Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals CoRR Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Justin K. Romberg, Richard G. Baraniuk
2009	J	`jnl`	Compressive Sensing DNA Microarrays. EURASIP J. Bioinform. Syst. Biol. Wei Dai, Mona A. Sheikh, Olgica Milenkovic, Richard G. Baraniuk
2009	—	`conf`	Compressive sensing of streams of pulses. Allerton Chinmay Hegde, Richard G. Baraniuk
2009	J	`jnl`	Distributed Compressive Sensing CoRR Dror Baron, Marco F. Duarte, Michael B. Wakin, Shriram Sarvotham, Richard G. Baraniuk
2009	—	`conf`	Model-based compressive sensing for signal ensembles. Allerton Marco F. Duarte, Volkan Cevher, Richard G. Baraniuk
2009	—	`conf`	Near-optimal Bayesian localization via incoherence and sparsity. IPSN Volkan Cevher, Petros Boufounos, Richard G. Baraniuk, Anna C. Gilbert, Martin J. Strauss
2009	J	`jnl`	Random Projections of Smooth Manifolds. Found. Comput. Math. Richard G. Baraniuk, Michael B. Wakin
2009	Misc	`conf`	Recovery of compressible signals in unions of subspaces. CISS Marco F. Duarte, Chinmay Hegde, Volkan Cevher, Richard G. Baraniuk
2009	J	`jnl`	Representation and Compression of Multidimensional Piecewise Functions Using Surflets. IEEE Trans. Inf. Theory Venkat Chandrasekaran, Michael B. Wakin, Dror Baron, Richard G. Baraniuk
2009	—	`conf`	Sparse Geodesic Paths. AAAI Fall Symposium: Manifold Learning and Its Applications Mark A. Davenport, Richard G. Baraniuk
2008	Misc	`conf`	1-Bit compressive sensing. CISS Petros Boufounos, Richard G. Baraniuk
2008	J	`jnl`	Bayesian Compressive Sensing via Belief Propagation CoRR Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
2008	J	`jnl`	Coherent Multiscale Image Processing Using Dual-Tree Quaternion Wavelets. IEEE Trans. Image Process. Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk
2008	J	`jnl`	Compressive Sampling [From the Guest Editors]. IEEE Signal Process. Mag. Richard G. Baraniuk, Emmanuel J. Candès, Robert D. Nowak, Martin Vetterli
2008	—	`conf`	Compressive Sensing for Background Subtraction. ECCV (2) Volkan Cevher, Aswin C. Sankaranarayanan, Marco F. Duarte, Dikpal Reddy, Richard G. Baraniuk, Rama Chellappa
2008	Misc	`conf`	Compressive sensing. CISS Richard G. Baraniuk
2008	—	`conf`	Distributed target localization via spatial sparsity. EUSIPCO Volkan Cevher, Marco F. Duarte, Richard G. Baraniuk
2008	J	`jnl`	Model-Based Compressive Sensing CoRR Richard G. Baraniuk, Volkan Cevher, Marco F. Duarte, Chinmay Hegde
2008	C	`conf`	On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion. ISCAS Stephen Pfetsch, Tamer Ragheb, Jason N. Laska, Hamid Nejati, Anna C. Gilbert, Martin Strauss, Richard G. Baraniuk, Yehia Massoud
2008	J	`jnl`	Peer Review Anew: Three Principles and a Case Study in Postpublication Quality Assurance. Proc. IEEE Christopher M. Kelty, C. Sidney Burrus, Richard G. Baraniuk
2008	—	`conf`	Probe Design for Compressive Sensing DNA Microarrays. BIBM Wei Dai, Olgica Milenkovic, Mona A. Sheikh, Richard G. Baraniuk
2008	Misc	`conf`	Reconstructing sparse signals from their zero crossings. ICASSP Petros Boufounos, Richard G. Baraniuk
2008	J	`jnl`	Single-pixel imaging via compressive sampling. IEEE Signal Process. Mag. Marco F. Duarte, Mark A. Davenport, Dharmpal Takhar, Jason N. Laska, Ting Sun, Kevin F. Kelly, Richard G. Baraniuk
2008	J	`jnl`	Sparse Coding via Thresholding and Local Competition in Neural Circuits. Neural Comput. Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen
2008	—	`conf`	Sparse Signal Recovery Using Markov Random Fields. NIPS Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Richard G. Baraniuk
2008	J	`jnl`	Viewpoint: Global warming toward open educational resources. Commun. ACM Richard G. Baraniuk, C. Sidney Burrus
2008	Misc	`conf`	Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model. ICASSP Marco F. Duarte, Michael B. Wakin, Richard G. Baraniuk
2007	—	`conf`	Blind Error-Free Detection of Transform-Domainwatermarks. ICIP (5) Mona A. Sheikh, Richard G. Baraniuk
2007	J	`jnl`	Compressive Sensing [Lecture Notes]. IEEE Signal Process. Mag. Richard G. Baraniuk
2007	J	`jnl`	IEEE-SPS and Connexions - An Open Access Education Collaboration [Society News]. IEEE Signal Process. Mag. Richard G. Baraniuk, C. Sidney Burrus, E. Joel Thierstein
2007	—	`conf`	Locally Competitive Algorithms for Sparse Approximation. ICIP (4) Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen
2007	—	`conf`	Multiscale Random Projections for Compressive Classification. ICIP (6) Marco F. Duarte, Mark A. Davenport, Michael B. Wakin, Jason N. Laska, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk
2007	J	`jnl`	On Nearly Orthogonal Lattice Bases and Random Lattices. SIAM J. Discret. Math. Ramesh Neelamani, Sanjeeb Dash, Richard G. Baraniuk
2007	B	`conf`	Quantization of Sparse Representations. DCC Petros Boufounos, Richard G. Baraniuk
2007	—	`conf`	Random Projections for Manifold Learning. NIPS Chinmay Hegde, Michael B. Wakin, Richard G. Baraniuk
2007	J	`jnl`	Texas Two-Step: A Framework for Optimal Multi-Input Single-Output Deconvolution. IEEE Trans. Image Process. Ramesh Neelamani, Max Deffenbaugh, Richard G. Baraniuk
2007	—	`conf`	The smashed filter for compressive classification and target recognition. Computational Imaging Mark A. Davenport, Marco F. Duarte, Michael B. Wakin, Jason N. Laska, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk
2007	C	`conf`	Theory and Implementation of an Analog-to-Information Converter using Random Demodulation. ISCAS Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tamer Ragheb, Richard G. Baraniuk, Yehia Massoud
2006	—	`conf`	A new compressive imaging camera architecture using optical-domain compression. Computational Imaging Dharmpal Takhar, Jason N. Laska, Michael B. Wakin, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Kevin F. Kelly, Richard G. Baraniuk
2006	B	`conf`	An Architecture for Compressive Imaging. ICIP Michael B. Wakin, Jason N. Laska, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk
2006	—	`conf`	An architecture for distributed wavelet analysis and processing in sensor networks. IPSN Raymond S. Wagner, Richard G. Baraniuk, Shu Du, David B. Johnson, Albert Cohen
2006	Misc	`conf`	Coding vs. Packet Retransmission over Noisy Channels. CISS Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
2006	—	`conf`	Controlling False Alarms With Support Vector Machines. ICASSP (5) Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
2006	—	`conf`	Distributed Wavelet De-Noising for Sensor Networks. CDC Raymond S. Wagner, Véronique Delouille, Richard G. Baraniuk
2006	J	`jnl`	Faster sequential universal coding via block partitioning. IEEE Trans. Inf. Theory Dror Baron, Richard G. Baraniuk
2006	J	`jnl`	JPEG compression history estimation for color images. IEEE Trans. Image Process. Ramesh Neelamani, Ricardo L. de Queiroz, Zhigang Fan, Sanjeeb Dash, Richard G. Baraniuk
2006	B	`conf`	Multiscale Image Disparity Estimation using the Quaternion Wavelet Transform. ICIP Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk
2006	J	`jnl`	Multiscale queueing analysis. IEEE/ACM Trans. Netw. Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk
2006	—	`conf`	Random Filters for Compressive Sampling and Reconstruction. ICASSP (3) Joel A. Tropp, Michael B. Wakin, Marco F. Duarte, Dror Baron, Richard G. Baraniuk
2006	—	`conf`	Random Projections of Signal Manifolds. ICASSP (5) Michael B. Wakin, Richard G. Baraniuk
2006	J	`jnl`	Robust Distributed Estimation Using the Embedded Subgraphs Algorithm. IEEE Trans. Signal Process. Véronique Delouille, Ramesh Neelamani, Richard G. Baraniuk
2006	—	`conf`	Sparse Signal Detection from Incoherent Projections. ICASSP (3) Marco F. Duarte, Mark A. Davenport, Michael B. Wakin, Richard G. Baraniuk
2006	B	`conf`	Sudocodes ߝ Fast Measurement and Reconstruction of Sparse Signals. ISIT Shriram Sarvotham, Dror Baron, Richard G. Baraniuk
2006	—	`conf`	Universal distributed sensing via random projections. IPSN Marco F. Duarte, Michael B. Wakin, Dror Baron, Richard G. Baraniuk
2006	J	`jnl`	Wavelet-domain approximation and compression of piecewise smooth images. IEEE Trans. Image Process. Michael B. Wakin, Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk
2005	—	`conf`	A multiscale data representation for distributed sensor networks. ICASSP (4) Raymond S. Wagner, Shriram Sarvotham, Richard G. Baraniuk
2005	B	`conf`	Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks. DCOSS Santashil PalChaudhuri, Rajnish Kumar, Richard G. Baraniuk, David B. Johnson
2005	—	`conf`	High-resolution navigation on non-differentiable image manifolds. ICASSP (5) Michael B. Wakin, David L. Donoho, Hyeokho Choi, Richard G. Baraniuk
2005	—	`conf`	Multiscale manifold representation and modeling. ICASSP (4) Hyeokho Choi, Richard G. Baraniuk
2005	J	`jnl`	Network and user driven alpha-beta on-off source model for network traffic. Comput. Networks Shriram Sarvotham, Rudolf H. Riedi, Richard G. Baraniuk
2005	—	`conf`	Recovery of Jointly Sparse Signals from Few Random Projections. NIPS Michael B. Wakin, Marco F. Duarte, Shriram Sarvotham, Dror Baron, Richard G. Baraniuk
2005	A*	`conf`	TCP-Africa: an adaptive and fair rapid increase rule for scalable TCP. INFOCOM R. King, Richard G. Baraniuk, Rudolf H. Riedi
2005	J	`jnl`	The dual-tree complex wavelet transform. IEEE Signal Process. Mag. Ivan W. Selesnick, Richard G. Baraniuk, Nick G. Kingsbury
2004	—	`conf`	Contraction, smoothness, and low-pass filtering. ICASSP (2) Mohammad Ali Khojastepour, Behnaam Aazhang, Richard G. Baraniuk
2004	B	`conf`	Delay-limited throughput maximization for fading channels using rate and power control. GLOBECOM Nadeem Ahmed, Mohammad Ali Khojestapour, Richard G. Baraniuk
2004	—	`conf`	Directional hypercomplex wavelets for multidimensional signal analysis and processing. ICASSP (3) Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk
2004	J	`jnl`	ForWaRD: Fourier-wavelet regularized deconvolution for ill-conditioned systems. IEEE Trans. Signal Process. Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniuk
2004	J	`jnl`	Joint signaling techniques and spectral optimization for symmetric bit-rate communication over self-NEXT-dominated channels. IEEE Trans. Commun. Rohit V. Gaikwad, Richard G. Baraniuk
2004	J	`jnl`	Locating Available Bandwidth Bottlenecks. IEEE Internet Comput. Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk
2004	J	`jnl`	Multiple wavelet basis image denoising using Besov ball projections. IEEE Signal Process. Lett. Hyeokho Choi, Richard G. Baraniuk
2004	—	`conf`	Non-redundant, linear-phase, semi-orthogonal, directional complex wavelets [image/video processing applications]. ICASSP (2) Felix C. A. Fernandes, Michael B. Wakin, Richard G. Baraniuk
2004	B	`conf`	Quaternion wavelets for image analysis and processing. ICIP Wai Lam Chan, Hyeokho Choi, Richard G. Baraniuk
2004	—	`conf`	Robust distributed estimation in sensor networks using the embedded polygons algorithm. IPSN Véronique Delouille, Ramesh Neelamani, Richard G. Baraniuk
2004	J	`jnl`	Sharing knowledge and building communities in signal processing. IEEE Signal Process. Mag. Richard G. Baraniuk, C. Sidney Burrus, Don H. Johnson, Douglas L. Jones
2004	A*	`conf`	Spatio-temporal available bandwidth estimation with STAB. SIGMETRICS Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk
2004	B	`conf`	Surflets: a sparse representation for multidimensional functions containing smooth discontinuities. ISIT Venkat Chandrasekaran, Michael B. Wakin, Dror Baron, Richard G. Baraniuk
2003	—	`conf`	Approximation and compression of piecewise smooth images using a wavelet/wedgelet geometric model. ICIP (1) Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk
2003	—	`conf`	Distributed image compression for sensor networks using correspondence analysis and super-resolution. ICIP (1) Raymond S. Wagner, Robert D. Nowak, Richard G. Baraniuk
2003	B	`conf`	Estimation-Quantization Geometry Coding Using Normal Meshes. DCC Sridhar Lavu, Hyeokho Choi, Richard G. Baraniuk
2003	B	`conf`	Geometry Compression of Normal Meshes Using Rate-Distortion Algorithms. Symposium on Geometry Processing Sridhar Lavu, Hyeokho Choi, Richard G. Baraniuk
2003	—	`conf`	JPEG compression history estimation for color images. ICIP (3) Ramesh Neelamani, Ricardo L. de Queiroz, Zhigang Fan, Richard G. Baraniuk
2003	C	`conf`	Multiscale geometric image processing. VCIP Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk
2003	J	`jnl`	Nonlinear wavelet transforms for image coding via lifting. IEEE Trans. Image Process. Roger L. Claypoole Jr., Geoffrey M. Davis, Wim Sweldens, Richard G. Baraniuk
2003	—	`conf`	Open-content signal processing laboratories in connexions. ICASSP (3) Swaroop Appadwedula, Richard G. Baraniuk, Matthew Berry, Mark D. Butala, Hyeokho Choi, Mark A. Haun, Douglas L. Jones, Michael L. Kramer, Dima Moussa, Lee C. Potter, Daniel Grobe Sachs, Brian Wade, Raymond S. Wagner
2003	—	`conf`	Orthogonal Hilbert transform filter banks and wavelets. ICASSP (6) Rutger L. van Spaendonck, Thierry Blu, Richard G. Baraniuk, Martin Vetterli
2002	Misc	`conf`	Additive and multiplicative mixture trees for network traffic modeling. ICASSP Shriram Sarvotham, Xin Wang, Rudolf H. Riedi, Richard G. Baraniuk
2002	B	`conf`	Asymptotic performance of transmit diversity via OFDM for multipath channels. GLOBECOM Nadeem Ahmed, Richard G. Baraniuk
2002	Misc	`conf`	Connexions: DSP education for a networked world. ICASSP Richard G. Baraniuk, C. Sidney Burrus, B. M. Hendricks, G. L. Henry, Alfred O. Hero III, Don H. Johnson, Douglas L. Jones, Julius Kusuma, Robert D. Nowak, J. E. Odegard, Lee C. Potter, Kannan Ramchandran, R. J. Reedstrom, Philip Schniter, Ivan W. Selesnick, Douglas B. Williams, W. L. Wilson
2002	B	`conf`	Image Compression using an Efficient Edge Cartoon + Texture Model. DCC Michael B. Wakin, Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk
2002	J	`jnl`	Multiscale nature of network traffic. IEEE Signal Process. Mag. Patrice Abry, Richard G. Baraniuk, Patrick Flandrin, Rudolf H. Riedi, Darryl Veitch
2002	—	`conf`	Multiscale wedgelet image analysis: fast decompositions and modeling. ICIP (3) Justin K. Romberg, Michael B. Wakin, Richard G. Baraniuk
2002	J	`jnl`	Near Best Tree Approximation. Adv. Comput. Math. Richard G. Baraniuk, Ronald A. DeVore, George Kyriazis, X. M. Yu
2002	—	`conf`	Rate-distortion optimized image compression using wedgelets. ICIP (3) Justin K. Romberg, Michael B. Wakin, Hyeokho Choi, Richard G. Baraniuk
2001	J	`jnl`	Bayesian tree-structured image modeling using wavelet-domain hidden Markov models. IEEE Trans. Image Process. Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk
2001	—	`conf`	Compression color space estimation of JPEG images using lattice basis reduction. ICIP (1) Ramesh Neelamani, Ricardo L. de Queiroz, Richard G. Baraniuk
2001	A	`conf`	Connection-level analysis and modeling of network traffic. Internet Measurement Workshop Shriram Sarvotham, Rudolf H. Riedi, Richard G. Baraniuk
2001	J	`jnl`	Hybrid linear/quadratic time-frequency attributes. IEEE Trans. Signal Process. Richard G. Baraniuk, Mark Coates, Philippe Steeghs
2001	C	`conf`	Lattice algorithms for compression color space estimation in JPEG images. IWCIA Ramesh Neelamani, Ricardo L. de Queiroz, Richard G. Baraniuk
2001	J	`jnl`	Measuring time-Frequency information content using the Rényi entropies. IEEE Trans. Inf. Theory Richard G. Baraniuk, Patrick Flandrin, Augustus J. E. M. Janssen, Olivier J. J. Michel
2001	—	`conf`	Multiscale edge grammars for complex wavelet transforms. ICIP (1) Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk
2001	—	`conf`	Multiscale image processing using normal triangulated meshes. ICIP (2) M. Jansen, Hyeokho Choi, Sridhar Lavu, Richard G. Baraniuk
2001	J	`jnl`	Multiscale image segmentation using wavelet-domain hidden Markov models. IEEE Trans. Image Process. Hyeokho Choi, Richard G. Baraniuk
2001	B	`conf`	Optimal transmit spectra for communication in the presence of crosstalk and imperfect echo cancellation. GLOBECOM Nadeem Ahmed, Richard G. Baraniuk, Donald P. Shaver
2001	Misc	`conf`	Wavelets and multifractals for network traffic modeling and inference. ICASSP Vinay J. Ribeiro, Rudolf H. Riedi, Richard G. Baraniuk
2000	—	`conf`	Bayesian Tree-Structured Image Modeling. SSIAI Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk
2000	Misc	`conf`	Hidden Markov tree modeling of complex wavelet transforms. ICASSP Hyeokho Choi, Justin K. Romberg, Richard G. Baraniuk, Nick G. Kingsbury
2000	Misc	`conf`	Hybrid linear/quadratic time-frequency attributes. ICASSP Richard G. Baraniuk, Mark Coates, Philippe Steeghs
2000	B	`conf`	Imaging with THZ Pulses. ICIP Timothy Dorney, Jon Johnson, Daniel M. Mittleman, Richard G. Baraniuk
2000	B	`conf`	Model-Based Inverse Halftoning with Wavelet-Vaguelette Deconvolution. ICIP Ramesh Neelamani, Robert D. Nowak, Richard G. Baraniuk
2000	B	`conf`	Multiscale Classification Using Complex Wavelets and Hidden Markov Tree Models. ICIP Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk, Nick G. Kingsbury
2000	A*	`conf`	Multiscale Queuing Analysis of Long-Range-Dependent Network Traffic. INFOCOM Vinay J. Ribeiro, Rudolf H. Riedi, Matthew S. Crouse, Richard G. Baraniuk
2000	—	`conf`	Multiscale document segmentation using wavelet-domain hidden Markov models. Document Recognition and Retrieval Hyeokho Choi, Richard G. Baraniuk
2000	—	`conf`	Spectroscopic Imaging Using Terahertz Time-Domain Signals. SSIAI Timothy Dorney, Richard G. Baraniuk, Daniel M. Mittleman, Robert D. Nowak
2000	Misc	`conf`	Wavelet folding and decorrelation across the scale. ICASSP Jun Feng Tian, Richard G. Baraniuk, Raymond O. Wells Jr., Damian M. Tan, Hong Ren Wu
1999	J	`jnl`	A Multifractal Wavelet Model with Application to Network Traffic. IEEE Trans. Inf. Theory Rudolf H. Riedi, Matthew S. Crouse, Vinay J. Ribeiro, Richard G. Baraniuk
1999	—	`conf`	Bayesian Wavelet-Domain Image Modeling Using Hidden Markov Trees. ICIP (1) Justin K. Romberg, Hyeokho Choi, Richard G. Baraniuk
1999	J	`jnl`	Hybrid linear/bilinear time-scale analysis. IEEE Trans. Signal Process. Martin Pasquier, Paulo Gonçalves, Richard G. Baraniuk
1999	Misc	`conf`	Interpolation and denoising of nonuniformly sampled data using wavelet-domain processing. ICASSP Hyeokho Choi, Richard G. Baraniuk
1999	—	`conf`	Multiple Basis Wavelet Denoising Using BESOV Projections. ICIP (1) Hyeokho Choi, Richard G. Baraniuk
1999	A*	`conf`	Simulation of nonGaussian Long-Range-Dependent Traffic Using Wavelets. SIGMETRICS Vinay J. Ribeiro, Rudolf H. Riedi, Matthew S. Crouse, Richard G. Baraniuk
1999	—	`conf`	Wavelet-Domain Regularized Deconvolution for ILL-Conditioned Systems. ICIP (1) Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniuk
1999	Misc	`conf`	Wavelet-based deconvolution for ill-conditioned systems. ICASSP Ramesh Neelamani, Hyeokho Choi, Richard G. Baraniuk
1999	J	`jnl`	Wavelet-based transformations for nonlinear signal processing. IEEE Trans. Signal Process. Robert D. Nowak, Richard G. Baraniuk
1999	J	`jnl`	Wavelet-domain filtering for photon imaging systems. IEEE Trans. Image Process. Robert D. Nowak, Richard G. Baraniuk
1998	B	`conf`	Adaptive Wavelet Transforms for Image Coding Using Lifting. Data Compression Conference Roger Claypool, Geoffrey M. Davis, Wim Sweldens, Richard G. Baraniuk
1998	Misc	`conf`	Adaptive wavelet transforms via lifting. ICASSP Roger L. Claypoole Jr., Richard G. Baraniuk, Robert D. Nowak
1998	J	`jnl`	Adaptive weighted highpass filters using multiscale analysis. IEEE Trans. Image Process. Robert D. Nowak, Richard G. Baraniuk
1998	J	`jnl`	Beyond time-frequency analysis: energy densities in one and many dimensions. IEEE Trans. Signal Process. Richard G. Baraniuk
1998	J	`jnl`	Joint Distributions of Arbitrary Variables Made Easy. Multidimens. Syst. Signal Process. Richard G. Baraniuk
1998	J	`jnl`	Pseudo affine Wigner distributions: definition and kernel formulation. IEEE Trans. Signal Process. Paulo Gonçalves, Richard G. Baraniuk
1998	Misc	`conf`	Simplified wavelet-domain hidden Markov models using contexts. ICASSP Matthew S. Crouse, Richard G. Baraniuk
1998	J	`jnl`	Wavelet-based statistical signal processing using hidden Markov models. IEEE Trans. Signal Process. Matthew S. Crouse, Robert D. Nowak, Richard G. Baraniuk
1997	Misc	`conf`	Improved type-based detection of analog signals. ICASSP Don H. Johnson, Paulo Gonçalves, Richard G. Baraniuk
1997	Misc	`conf`	Signal estimation using wavelet-Markov models. ICASSP Matthew S. Crouse, Richard G. Baraniuk, Robert D. Nowak
1997	Misc	`conf`	Wavelet-based transformations for nonlinear signal processing. ICASSP Robert D. Nowak, Richard G. Baraniuk
1996	J	`jnl`	A limitation of the kernel method for joint distributions of arbitrary variables. IEEE Signal Process. Lett. Richard G. Baraniuk
1996	J	`jnl`	A pseudo-Bertrand distribution for time-scale analysis. IEEE Signal Process. Lett. Paulo Gonçalves, Richard G. Baraniuk
1996	J	`jnl`	Covariant time-frequency representations through unitary equivalence. IEEE Signal Process. Lett. Richard G. Baraniuk
1996	J	`jnl`	Myoelectric teleoperation of a complex robotic hand. IEEE Trans. Robotics Autom. Kristin A. Farry, Ian D. Walker, Richard G. Baraniuk
1996	Misc	`conf`	Optimal phase kernels for time-frequency analysis. ICASSP L. Fridtjof Wisur-Olsen, Richard G. Baraniuk
1996	Misc	`conf`	Pseudo affine Wigner distributions. ICASSP Paulo Gonçalves, Richard G. Baraniuk
1996	J	`jnl`	Wigner-based formulation of the chirplet transform. IEEE Trans. Signal Process. Richard G. Baraniuk, Douglas L. Jones
1995	J	`jnl`	An adaptive optimal-kernel time-frequency representation. IEEE Trans. Signal Process. Douglas L. Jones, Richard G. Baraniuk
1995	Misc	`conf`	Marginals vs. covariance in joint distribution theory. ICASSP Richard G. Baraniuk
1995	J	`jnl`	On joint distributions for arbitrary variables. IEEE Signal Process. Lett. Richard G. Baraniuk, Leon Cohen
1995	J	`jnl`	Unitary equivalence: a new twist on signal processing. IEEE Trans. Signal Process. Richard G. Baraniuk, Douglas L. Jones
1995	—	`conf`	Warping time-frequency and time-scale representations to match signals. Visual Information Processing Richard G. Baraniuk
1994	J	`jnl`	A signal-dependent time-frequency representation: fast algorithm for optimal kernel design. IEEE Trans. Signal Process. Richard G. Baraniuk, Douglas L. Jones
1994	J	`jnl`	A simple scheme for adapting time-frequency representations. IEEE Trans. Signal Process. Douglas L. Jones, Richard G. Baraniuk
1994	—	`conf`	Beyond time-frequency analysis: energy densities in one and many dimensions. ICASSP (3) Richard G. Baraniuk
1994	—	`conf`	Time-frequency complexity and information. ICASSP (3) Patrick Flandrin, Richard G. Baraniuk, Olivier J. J. Michel
1994	—	`conf`	Wavelet Soft-Thresholding of Time-Frequency Representations. ICIP (1) Richard G. Baraniuk
1993	J	`jnl`	A signal-dependent time-frequency representation: optimal kernel design. IEEE Trans. Signal Process. Richard G. Baraniuk, Douglas L. Jones
1993	—	`conf`	An adaptive optimal-kernel time-frequency representation. ICASSP (4) Douglas L. Jones, Richard G. Baraniuk
1993	J	`jnl`	Shear madness: new orthonormal bases and frames using chirp functions. IEEE Trans. Signal Process. Richard G. Baraniuk, Douglas L. Jones
1993	J	`jnl`	Signal-dependent time-frequency analysis using a radially Gaussian kernel. Signal Process. Richard G. Baraniuk, Douglas L. Jones
1993	—	`conf`	Warped wavelet bases: unitary equivalence and signal processing. ICASSP (3) Richard G. Baraniuk, Douglas L. Jones
1992	Misc	`conf`	New dimensions in wavelet analysis. ICASSP Richard G. Baraniuk, Douglas L. Jones
1992	—	`—`	Shear Madness: Signal-Dependent and Metaplectic Time-Frequency Representations Richard G. Baraniuk
1991	Misc	`conf`	A radially-Gaussian, signal-dependent time-frequency representation. ICASSP Richard G. Baraniuk, Douglas L. Jones
1989	J	`jnl`	Matrix based computation of floating-point roundoff noise. IEEE Trans. Acoust. Speech Signal Process. Barry D. Van Veen, Richard G. Baraniuk