Jayaraman J. Thiagarajan

247 papers A* 19A 15B 9C 8Misc 30Journal 134Unranked 29

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Conformal Edge-Weight Prediction in Latent Space. SDM Akash Choudhuri, Yongjian Zhong, Mehrdad Moharrami, Christine Klymko, Mark Heimann, Jayaraman J. Thiagarajan, Bijaya Adhikari
2025	Misc	`conf`	Leveraging Registers in Vision Transformers for Robust Adaptation. ICASSP Srikar Yellapragada, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Wesam A. Sakla, Yang Liu, Yamen Mubarka, Dimitris Samaras, Jayaraman J. Thiagarajan
2025	J	`jnl`	Leveraging Registers in Vision Transformers for Robust Adaptation. CoRR Srikar Yellapragada, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Wesam A. Sakla, Yang Liu, Yamen Mubarka, Dimitris Samaras, Jayaraman J. Thiagarajan
2025	A	`conf`	ModelX : A Novel Transfer Learning Approach Across Heterogeneous Datasets. HPDC Arunavo Dey, Neil Antony, Aakash Raj Dhakal, Kowshik Thopalli, Jayaraman J. Thiagarajan, Tapasya Patki, Aniruddha Marathe, Tom Scogland, Jae-Seung Yeom, Tanzima Z. Islam
2025	J	`jnl`	Multi-fidelity Reinforcement Learning Control for Complex Dynamical Systems. CoRR Luning Sun, Xin-Yang Liu, Siyan Zhao, Aditya Grover, Jian-Xun Wang, Jayaraman J. Thiagarajan
2025	Misc	`conf`	On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation. ICASSP Banooqa H. Banday, Kowshik Thopalli, Tanzima Z. Islam, Jayaraman J. Thiagarajan
2025	J	`jnl`	Structure-Aware Representation Learning for Effective Performance Prediction. Concurr. Comput. Pract. Exp. Tarek Ramadan, Nathan Pinnow, Chase Phelps, Jayaraman J. Thiagarajan, Tanzima Z. Islam
2025	—	`conf`	The Surprising Utility of Group Partitioning in Improving Conformal Prediction of Visual Classifiers under Distributional Shifts. CVPR Workshops Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan
2024	—	`conf`	'Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning. CVPR Workshops Joshua Feinglass, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Yezhou Yang
2024	J	`jnl`	'Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning. CoRR Joshua Feinglass, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Yezhou Yang
2024	A*	`conf`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. ICLR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024	J	`jnl`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024	—	`conf`	DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. ECCV (79) Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan
2024	J	`jnl`	DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation. CoRR Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan
2024	J	`jnl`	Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization. CoRR Hongjun Choi, Jayaraman J. Thiagarajan, Ruben Glatt, Shusen Liu
2024	Misc	`conf`	Exploring the Utility of Clip Priors for Visual Relationship Prediction. ICASSP Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
2024	Misc	`conf`	On Estimating Link Prediction Uncertainty Using Stochastic Centering. ICASSP Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2024	J	`jnl`	On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation. CoRR Banooqa H. Banday, Kowshik Thopalli, Tanzima Z. Islam, Jayaraman J. Thiagarajan
2024	A*	`conf`	On the Use of Anchoring for Training Vision Models. NeurIPS Vivek Sivaraman Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam A. Sakla, Jayaraman J. Thiagarajan
2024	J	`jnl`	On the Use of Anchoring for Training Vision Models. CoRR Vivek Sivaraman Narayanaswamy, Kowshik Thopalli, Rushil Anirudh, Yamen Mubarka, Wesam A. Sakla, Jayaraman J. Thiagarajan
2024	A*	`conf`	PAGER: Accurate Failure Characterization in Deep Regression Models. ICML Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2024	J	`jnl`	Speeding Up Image Classifiers with Little Companions. CoRR Yang Liu, Kowshik Thopalli, Jayaraman J. Thiagarajan
2024	Misc	`conf`	The Double-Edged Sword Of Ai Safety: Balancing Anomaly Detection and OOD Generalization Via Model Anchoring. ICASSP Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Jayaraman J. Thiagarajan
2024	J	`jnl`	Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data. Mach. Learn. Sci. Technol. Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
2023	Misc	`conf`	A Closer Look At Scoring Functions And Generalization Prediction. ICASSP Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	A*	`conf`	A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. ICLR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. CoRR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	A Closer Look at Scoring Functions and Generalization Prediction. CoRR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2023	J	`jnl`	CREPE: Learnable Prompting With CLIP Improves Visual Relationship Prediction. CoRR Rakshith Subramanyam, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
2023	A	`conf`	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. WACV Rakshith Subramanyam, Mark Heimann, T. S. Jayram, Rushil Anirudh, Jayaraman J. Thiagarajan
2023	A*	`conf`	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models. CVPR Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
2023	J	`jnl`	Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models. CoRR Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong
2023	A*	`conf`	DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. ICCV Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim
2023	—	`conf`	Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. ICCV (Workshops) Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan
2023	J	`jnl`	Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson
2023	A	`conf`	Improving Diversity with Adversarially Learned Transformations for Domain Generalization. WACV Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
2023	J	`jnl`	Improving Object Detectors by Exploiting Bounding Boxes for Augmentation Design. IEEE Access S. Devi, Kowshik Thopalli, R. Dayana, P. Malarvezhi, Jayaraman J. Thiagarajan
2023	—	`conf`	InterAug: A Tuning-Free Augmentation Policy for Data-Efficient and Robust Object Detection. ICCV (Workshops) Kowshik Thopalli, Devi S, Jayaraman J. Thiagarajan
2023	—	`conf`	Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
2023	J	`jnl`	PAGER: A Framework for Failure Analysis of Deep Regression Models. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2023	Misc	`conf`	Single-Shot Domain Adaptation via Target-Aware Generative Augmentations. ICASSP Rakshith Subramanyam, Kowshik Thopalli, Spring Berman, Pavan K. Turaga, Jayaraman J. Thiagarajan
2023	A*	`conf`	Target-Aware Generative Augmentations for Single-Shot Adaptation. ICML Kowshik Thopalli, Rakshith Subramanyam, Pavan K. Turaga, Jayaraman J. Thiagarajan
2023	J	`jnl`	Target-Aware Generative Augmentations for Single-Shot Adaptation. CoRR Kowshik Thopalli, Rakshith Subramanyam, Pavan K. Turaga, Jayaraman J. Thiagarajan
2023	J	`jnl`	The Surprising Effectiveness of Deep Orthogonal Procrustes Alignment in Unsupervised Domain Adaptation. IEEE Access Kowshik Thopalli, Rushil Anirudh, Pavan K. Turaga, Jayaraman J. Thiagarajan
2023	J	`jnl`	Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data. CoRR Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh
2022	J	`jnl`	A biology-informed similarity metric for simulated patches of human cell membrane. Mach. Learn. Sci. Technol. Harsh Bhatia, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Tomas Oppelstrup, Helgi I. Ingólfsson, Felice C. Lightstone, Peer-Timo Bremer
2022	—	`conf`	Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. Healthcare AI and COVID-19 Workshop Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2022	J	`jnl`	Analyzing Data-Centric Properties for Contrastive Learning on Graphs. CoRR Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
2022	A*	`conf`	Analyzing Data-Centric Properties for Graph Contrastive Learning. NeurIPS Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
2022	J	`jnl`	Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification. CoRR Rakshith Subramanyam, Mark Heimann, Jayram S. Thathachar, Rushil Anirudh, Jayaraman J. Thiagarajan
2022	J	`jnl`	DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction. CoRR Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He, K. Aditya Mohan, Ulugbek S. Kamilov, Hyojin Kim
2022	C	`conf`	Domain Alignment Meets Fully Test-Time Adaptation. ACML Kowshik Thopalli, Pavan K. Turaga, Jayaraman J. Thiagarajan
2022	J	`jnl`	Domain Alignment Meets Fully Test-Time Adaptation. CoRR Kowshik Thopalli, Pavan K. Turaga, Jayaraman J. Thiagarajan
2022	J	`jnl`	Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. J. Luc Peterson, Benjamin Bay, Joe Koning, Peter B. Robinson, Jessica Semler, Jeremy White, Rushil Anirudh, Kevin Athey, Peer-Timo Bremer, Francesco Di Natale, David Fox, Jim A. Gaffney, Sam Ade Jacobs, Bhavya Kailkhura, Bogdan Kustowski, Steve H. Langer, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
2022	J	`jnl`	Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety. CoRR Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2022	A*	`conf`	Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images. ICML Rakshith Subramanyam, Vivek Sivaraman Narayanaswamy, Mark Naufel, Andreas Spanias, Jayaraman J. Thiagarajan
2022	J	`jnl`	Improving Diversity with Adversarially Learned Transformations for Domain Generalization. CoRR Tejas Gokhale, Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Chitta Baral, Yezhou Yang
2022	J	`jnl`	Improving Single-Stage Object Detectors for Nighttime Pedestrian Detection. Int. J. Pattern Recognit. Artif. Intell. Kowshik Thopalli, Jayaraman J. Thiagarajan
2022	J	`jnl`	Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors. Int. J. Virtual Pers. Learn. Environ. Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Ramamurthy, Andreas Spanias, Mahesh K. Banavar, Abhinav Dixit, Jie Fan, Mohit Malu, Kristen Jaskie, Sunil Rao, Uday Shankar Shanthamallu, Vivek Sivaraman Narayanaswamy, Sameeksha Katoch
2022	—	`conf`	Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. Healthcare AI and COVID-19 Workshop Jayaraman J. Thiagarajan, Rushil Anirudh, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2022	J	`jnl`	On-the-fly Object Detection using StyleGAN with CLIP Guidance. CoRR Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam A. Sakla, Rushil Anirudh
2022	C	`conf`	Out of Distribution Detection via Neural Network Anchoring. ACML Rushil Anirudh, Jayaraman J. Thiagarajan
2022	J	`jnl`	Out of Distribution Detection via Neural Network Anchoring. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan
2022	Misc	`conf`	Predicting the Generalization Gap in Deep Models using Anchoring. ICASSP Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Irene Kim, Yamen Mubarka, Andreas Spanias, Jayaraman J. Thiagarajan
2022	J	`jnl`	Revisiting Deep Subspace Alignment for Unsupervised Domain Adaptation. CoRR Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan K. Turaga
2022	J	`jnl`	Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. CoRR Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
2022	A*	`conf`	Single Model Uncertainty Estimation via Stochastic Data Centering. NeurIPS Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer
2022	J	`jnl`	Single Model Uncertainty Estimation via Stochastic Data Centering. CoRR Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Peer-Timo Bremer
2022	J	`jnl`	Single-Shot Domain Adaptation via Target-Aware Generative Augmentation. CoRR Rakshith Subramanyam, Kowshik Thopalli, Spring Berman, Pavan K. Turaga, Jayaraman J. Thiagarajan
2022	Misc	`conf`	Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2022	J	`jnl`	Suppressing simulation bias in multi-modal data using transfer learning. Mach. Learn. Sci. Technol. Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Michael K. G. Kruse, Ryan Nora
2021	A*	`conf`	Accurate and Robust Feature Importance Estimation under Distribution Shifts. AAAI Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias
2021	A*	`conf`	Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. AAAI Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang
2021	J	`jnl`	COVID-19 detection using cough sound analysis and deep learning algorithms. Intell. Decis. Technol. Sunil Rao, Vivek Sivaraman Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, Andreas Spanias
2021	B	`conf`	College Life is Hard! - Shedding Light on Stress Prediction for Autistic College Students using Data-Driven Analysis. COMPSAC Tanzima Z. Islam, Philip Wu Liang, Forest Sweeney, Cody Pranger, Jayaraman J. Thiagarajan, Moushumi Sharmin, Shameem Ahmed
2021	B	`conf`	Comparative Code Structure Analysis using Deep Learning for Performance Prediction. ISPASS Tarek Ramadan, Tanzima Z. Islam, Chase Phelps, Nathan Pinnow, Jayaraman J. Thiagarajan
2021	J	`jnl`	Comparative Code Structure Analysis using Deep Learning for Performance Prediction. CoRR Nathan Pinnow, Tarek Ramadan, Tanzima Z. Islam, Chase Phelps, Jayaraman J. Thiagarajan
2021	J	`jnl`	Coverage-Based Designs Improve Sample Mining and Hyperparameter Optimization. IEEE Trans. Neural Networks Learn. Syst. Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Cihan Tepedelenlioglu, Andreas Spanias
2021	—	`conf`	Deep Learning with hyper-parameter tuning for COVID-19 Cough Detection. IISA Sunil Rao, Vivek Sivaraman Narayanaswamy, Michael Esposito, Jayaraman J. Thiagarajan, Andreas Spanias
2021	A*	`conf`	Designing Counterfactual Generators using Deep Model Inversion. NeurIPS Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
2021	J	`jnl`	Designing Counterfactual Generators using Deep Model Inversion. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
2021	J	`jnl`	Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion. CoRR Ankita Shukla, Rushil Anirudh, Eugene Kur, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears, Tammy Ma, Pavan K. Turaga
2021	J	`jnl`	Improving Multi-Domain Generalization through Domain Re-labeling. CoRR Kowshik Thopalli, Sameeksha Katoch, Andreas Spanias, Pavan K. Turaga, Jayaraman J. Thiagarajan
2021	J	`jnl`	Loss Estimators Improve Model Generalization. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Deepta Rajan, Andreas Spanias
2021	J	`jnl`	MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis. Frontiers Big Data Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Peer-Timo Bremer
2021	J	`jnl`	MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson
2021	A	`conf`	On the Design of Deep Priors for Unsupervised Audio Restoration. Interspeech Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2021	J	`jnl`	On the Design of Deep Priors for Unsupervised Audio Restoration. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2021	J	`jnl`	Preventing Failures by Dataset Shift Detection in Safety-Critical Graph Applications. Frontiers Artif. Intell. Hoseung Song, Jayaraman J. Thiagarajan, Bhavya Kailkhura
2021	—	`conf`	Self-training with improved regularization for sample-efficient chest x-ray classification. Computer-Aided Diagnosis Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap
2021	J	`jnl`	Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data. CoRR Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan
2021	A*	`conf`	Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks. AAAI Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias
2021	Misc	`conf`	Using Deep Image Priors to Generate Counterfactual Explanations. ICASSP Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2021	J	`jnl`	Δ-UQ: Accurate Uncertainty Quantification via Anchor Marginalization. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan
2020	Misc	`conf`	A Regularized Attention Mechanism for Graph Attention Networks. ICASSP Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias
2020	A*	`conf`	A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning. NeurIPS Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Jize Zhang, Yi Zhou, Timo Bremer
2020	J	`jnl`	Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2020	J	`jnl`	Accurate and Robust Feature Importance Estimation under Distribution Shifts. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias
2020	J	`jnl`	Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification. CoRR Bindya Venkatesh, Jayaraman J. Thiagarajan
2020	J	`jnl`	Attribute-Guided Adversarial Training for Robustness to Natural Perturbations. CoRR Tejas Gokhale, Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Chitta Baral, Yezhou Yang
2020	A*	`conf`	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. AAAI Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer
2020	J	`jnl`	Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration. CoRR Bindya Venkatesh, Jayaraman J. Thiagarajan, Kowshik Thopalli, Prasanna Sattigeri
2020	J	`jnl`	Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models. CoRR Jayaraman J. Thiagarajan, Prasanna Sattigeri, Deepta Rajan, Bindya Venkatesh
2020	J	`jnl`	Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models. CoRR Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, Brian K. Spears
2020	J	`jnl`	GrAMME: Semisupervised Learning Using Multilayered Graph Attention Models. IEEE Trans. Neural Networks Learn. Syst. Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2020	J	`jnl`	Improved surrogates in inertial confinement fusion with manifold and cycle consistencies. Proc. Natl. Acad. Sci. USA Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears
2020	—	`conf`	Improving Reliability of Clinical Models Using Prediction Calibration. UNSURE/GRAIL@MICCAI Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri
2020	Misc	`conf`	Learn-By-Calibrating: Using Calibration As A Training Objective. ICASSP Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
2020	J	`jnl`	Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. CoRR Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz
2020	J	`jnl`	Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations. CoRR Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan
2020	J	`jnl`	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. Int. J. Comput. Vis. Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Peer-Timo Bremer
2020	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom
2020	J	`jnl`	Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification. CoRR Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap
2020	A	`conf`	The Case of Performance Variability on Dragonfly-based Systems. IPDPS Abhinav Bhatele, Jayaraman J. Thiagarajan, Taylor L. Groves, Rushil Anirudh, Staci A. Smith, Brandon Cook, David K. Lowenthal
2020	Misc	`conf`	Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions. ACSSC Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura
2020	J	`jnl`	Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks. CoRR Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias
2020	J	`jnl`	Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections. Mach. Learn. Sci. Technol. Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2020	A	`conf`	Unsupervised Audio Source Separation Using Generative Priors. INTERSPEECH Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias
2020	J	`jnl`	Unsupervised Audio Source Separation using Generative Priors. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh, Andreas Spanias
2020	J	`jnl`	Using Deep Image Priors to Generate Counterfactual Explanations. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
2019	J	`jnl`	A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis. CoRR Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Peer-Timo Bremer
2019	J	`jnl`	Audio Source Separation via Multi-Scale Learning with Dilated Dense U-Nets. CoRR Vivek Sivaraman Narayanaswamy, Sameeksha Katoch, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2019	Misc	`conf`	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. ICASSP Rushil Anirudh, Jayaraman J. Thiagarajan
2019	J	`jnl`	Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. CoRR Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer
2019	Misc	`conf`	Designing an Effective Metric Learning Pipeline for Speaker Diarization. ICASSP Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2019	C	`conf`	Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation. ICMLA Jayaraman J. Thiagarajan, Satyananda Kashyap, Alexandros Karargyris
2019	J	`jnl`	Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation. CoRR Jayaraman J. Thiagarajan, Satyananda Kashyap, Alexandros Karargyris
2019	J	`jnl`	Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Brian K. Spears
2019	J	`jnl`	Function Preserving Projection for Scalable Exploration of High-Dimensional Data. CoRR Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2019	J	`jnl`	Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning. CoRR Bindya Venkatesh, Jayaraman J. Thiagarajan
2019	—	`conf`	Improved Deep Embeddings for Inferencing with Multi-Layered Graphs. IEEE BigData Huan Song, Jayaraman J. Thiagarajan
2019	J	`jnl`	Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears
2019	J	`jnl`	Improving Limited Angle CT Reconstruction with a Robust GAN Prior. CoRR Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley
2019	J	`jnl`	Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning. CoRR Sameeksha Katoch, Kowshik Thopalli, Jayaraman J. Thiagarajan, Pavan K. Turaga, Andreas Spanias
2019	J	`jnl`	Learn-By-Calibrating: Using Calibration as a Training Objective. CoRR Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
2019	J	`jnl`	Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452). Dagstuhl Reports Enrico Bertini, Peer-Timo Bremer, Daniela Oelke, Jayaraman J. Thiagarajan
2019	J	`jnl`	Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
2019	J	`jnl`	MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
2019	Misc	`conf`	Multiple Subspace Alignment Improves Domain Adaptation. ICASSP Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga
2019	C	`conf`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer
2019	J	`jnl`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears
2019	A	`conf`	Performance optimality or reproducibility: that is the question. SC Tapasya Patki, Jayaraman J. Thiagarajan, Alexis Ayala, Tanzima Z. Islam
2019	J	`jnl`	SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation. CoRR Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan K. Turaga
2019	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer
2019	Misc	`conf`	Understanding Deep Neural Networks through Input Uncertainties. ICASSP Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer
2019	Misc	`conf`	Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum. ICASSP Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer
2018	—	`conf`	A Generative Modeling Approach to Limited Channel ECG Classification. EMBC Deepta Rajan, Jayaraman J. Thiagarajan
2018	J	`jnl`	A Generative Modeling Approach to Limited Channel ECG Classification. CoRR Deepta Rajan, Jayaraman J. Thiagarajan
2018	J	`jnl`	A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms. J. Mach. Learn. Res. Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer
2018	J	`jnl`	An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
2018	A*	`conf`	Attend and Diagnose: Clinical Time Series Analysis Using Attention Models. AAAI Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias
2018	J	`jnl`	Attention Models with Random Features for Multi-layered Graph Embeddings. CoRR Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2018	A	`conf`	Bootstrapping Parameter Space Exploration for Fast Tuning. ICS Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin
2018	J	`jnl`	Can Deep Clinical Models Handle Real-World Domain Shifts? CoRR Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri
2018	J	`jnl`	Controlled Random Search Improves Sample Mining and Hyper-Parameter Optimization. CoRR Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2018	J	`jnl`	Designing an Effective Metric Learning Pipeline for Speaker Diarization. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song, Andreas Spanias
2018	J	`jnl`	Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. Comput. Graph. Forum Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
2018	J	`jnl`	Improved Community Detection using Deep Embeddings from Multilayer Graphs. CoRR Huan Song, Jayaraman J. Thiagarajan
2018	J	`jnl`	Improving Robustness of Attention Models on Graphs. CoRR Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias
2018	A*	`conf`	Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CVPR Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Timo Bremer
2018	J	`jnl`	MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer
2018	A	`conf`	Mitigating inter-job interference using adaptive flow-aware routing. SC Staci A. Smith, Clara E. Cromey, David K. Lowenthal, Jens Domke, Nikhil Jain, Jayaraman J. Thiagarajan, Abhinav Bhatele
2018	J	`jnl`	Multiple Subspace Alignment Improves Domain Adaptation. CoRR Kowshik Thopalli, Rushil Anirudh, Jayaraman J. Thiagarajan, Pavan K. Turaga
2018	J	`jnl`	Optimizing Kernel Machines Using Deep Learning. IEEE Trans. Neural Networks Learn. Syst. Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2018	A	`conf`	PADDLE: Performance Analysis Using a Data-Driven Learning Environment. IPDPS Jayaraman J. Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, Nikhil Jain, Tanzima Z. Islam, Abhinav Bhatele, Jae-Seung Yeom, Todd Gamblin
2018	A	`conf`	Triplet Network with Attention for Speaker Diarization. INTERSPEECH Huan Song, Megan M. Willi, Jayaraman J. Thiagarajan, Visar Berisha, Andreas Spanias
2018	J	`jnl`	Triplet Network with Attention for Speaker Diarization. CoRR Huan Song, Megan M. Willi, Jayaraman J. Thiagarajan, Visar Berisha, Andreas Spanias
2018	J	`jnl`	Understanding Deep Neural Networks through Input Uncertainties. CoRR Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer
2018	J	`jnl`	Unsupervised Dimension Selection using a Blue Noise Spectrum. CoRR Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer
2018	J	`jnl`	Visual Exploration of Semantic Relationships in Neural Word Embeddings. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Vivek Srikumar, Bei Wang, Yarden Livnat, Valerio Pascucci
2017	J	`jnl`	A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms. CoRR Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer
2017	Misc	`conf`	A deep learning approach to multiple kernel fusion. ICASSP Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2017	J	`jnl`	Attend and Diagnose: Clinical Time Series Analysis using Attention Models. CoRR Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias
2017	J	`jnl`	Bootstrapping Graph Convolutional Neural Networks for Autism Spectrum Disorder Classification. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan
2017	J	`jnl`	Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm. CoRR Youzuo Lin, Shusen Wang, Jayaraman J. Thiagarajan, George Guthrie, David Coblentz
2017	J	`jnl`	Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. CoRR Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
2017	J	`jnl`	Influential Sample Selection: A Graph Signal Processing Approach. CoRR Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Timo Bremer
2017	—	`conf`	Learning Robust Representations for Computer Vision. ICCV Workshops Peng Zheng, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy
2017	J	`jnl`	Learning Robust Representations for Computer Vision. CoRR Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan
2017	J	`jnl`	Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CoRR Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Peer-Timo Bremer
2017	J	`jnl`	Optimizing Kernel Machines using Deep Learning. CoRR Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2017	A	`conf`	Performance modeling under resource constraints using deep transfer learning. SC Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin
2017	—	`conf`	Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization. CVPR Workshops Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2016	J	`jnl`	A Deep Learning Approach To Multiple Kernel Fusion. CoRR Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2016	A	`conf`	A machine learning framework for performance coverage analysis of proxy applications. SC Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin
2016	B	`conf`	Auto-context modeling using multiple Kernel learning. ICIP Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2016	Misc	`conf`	Beyond L2-loss functions for learning sparse models. ICASSP Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan
2016	Misc	`conf`	Consensus inference on mobile phone sensors for activity recognition. ICASSP Huan Song, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias, Pavan K. Turaga
2016	—	`conf`	Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices. PMBS@SC Jae-Seung Yeom, Jayaraman J. Thiagarajan, Abhinav Bhatele, Greg Bronevetsky, Tzanio V. Kolev
2016	—	`conf`	Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models. NIPS Time Series Workshop Qunwei Li, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Zhenliang Zhang, Pramod K. Varshney
2016	J	`jnl`	Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models. CoRR Qunwei Li, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Zhenliang Zhang, Pramod K. Varshney
2016	—	`conf`	Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data. Computer-Aided Diagnosis Rushil Anirudh, Jayaraman J. Thiagarajan, Timo Bremer, Hyojin Kim
2016	B	`conf`	Measuring glomerular number from kidney MRI images. Image Processing Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Berkay Kanberoglu, David H. Frakes, Kevin Bennett, Andreas Spanias
2016	—	`conf`	Robust Local Scaling Using Conditional Quantiles of Graph Similarities. ICDM Workshops Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura
2016	—	`conf`	Sparsifying Word Representations for Deep Unordered Sentence Modeling. Rep4NLP@ACL Prasanna Sattigeri, Jayaraman J. Thiagarajan
2016	J	`jnl`	Stair blue noise sampling. ACM Trans. Graph. Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Pramod K. Varshney
2016	Misc	`conf`	Theoretical guarantees for poisson disk sampling using pair correlation function. ICASSP Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Pramod K. Varshney
2016	J	`jnl`	TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning. CoRR Jayaraman J. Thiagarajan, Bhavya Kailkhura, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy
2016	J	`jnl`	Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach. CoRR Prashant Khanduri, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Pramod K. Varshney
2016	J	`jnl`	Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach. IEEE Signal Process. Lett. Prashant Khanduri, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Pramod K. Varshney
2015	A*	`conf`	A Randomized Ensemble Approach to Industrial CT Segmentation. ICCV Hyojin Kim, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2015	A	`conf`	Identifying the Culprits Behind Network Congestion. IPDPS Abhinav Bhatele, Andrew R. Titus, Jayaraman J. Thiagarajan, Nikhil Jain, Todd Gamblin, Peer-Timo Bremer, Martin Schulz, Laxmikant V. Kalé
2015	J	`jnl`	Learning Stable Multilevel Dictionaries for Sparse Representations. IEEE Trans. Neural Networks Learn. Syst. Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2015	Misc	`conf`	Subspace learning using consensus on the grassmannian manifold. ICASSP Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy
2015	J	`jnl`	Undergraduate Signal Processing Laboratories for the Android Operating System. CoRR Suhas Ranganath, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Mahesh K. Banavar, Andreas Spanias
2015	J	`jnl`	Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections. Comput. Graph. Forum Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci
2014	Misc	`conf`	A scalable feature learning and tag prediction framework for natural environment sounds. ACSSC Prasanna Sattigeri, Jayaraman J. Thiagarajan, Mohit Shah, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2014	B	`conf`	Automatic image annotation using inverse maps from semantic embeddings. ICIP Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Peer-Timo Bremer, Andreas Spanias
2014	J	`jnl`	Beyond L2-Loss Functions for Learning Sparse Models. CoRR Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Jayaraman J. Thiagarajan
2014	—	`conf`	Computing persistent homology under random projection. SSP Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Jayaraman J. Thiagarajan
2014	Misc	`conf`	Consensus inference with multilayer graphs for multi-modal data. ACSSC Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Rahul Sridhar, Premnishanth Kothandaraman, Ramanathan Nachiappan
2014	—	`book`	Image Understanding Using Sparse Representations Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Pavan K. Turaga, Andreas Spanias
2014	B	`conf`	Image segmentation using consensus from hierarchical segmentation ensembles. ICIP Hyojin Kim, Jayaraman J. Thiagarajan, Peer-Timo Bremer
2014	J	`jnl`	Kernel Sparse Models for Automated Tumor Segmentation. Int. J. Artif. Intell. Tools Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Andreas Spanias, Anup Puri, David H. Frakes
2014	J	`jnl`	Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning. IEEE Trans. Image Process. Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2014	Misc	`conf`	Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation. ICASSP Jayaraman J. Thiagarajan, Peer-Timo Bremer, Karthikeyan Natesan Ramamurthy
2014	—	`conf`	Multivariate volume visualization through dynamic projections. LDAV Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci
2014	J	`jnl`	Recovering non-negative and combined sparse representations. Digit. Signal Process. Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias
2013	Misc	`conf`	A heterogeneous dictionary model for representation and recognition of human actions. ICASSP Rushil Anirudh, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Pavan K. Turaga, Andreas Spanias
2013	Misc	`conf`	Boosted dictionaries for image restoration based on sparse representations. ICASSP Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, Prasanna Sattigeri
2013	J	`jnl`	Ensemble Sparse Models for Image Analysis CoRR Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2013	J	`jnl`	Kernel Sparse Models for Automated Tumor Segmentation CoRR Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Anup Puri, David H. Frakes, Andreas Spanias
2013	J	`jnl`	Learning Stable Multilevel Dictionaries for Sparse Representation of Images CoRR Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2013	J	`jnl`	Mixing matrix estimation using discriminative clustering for blind source separation. Digit. Signal Process. Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2013	J	`jnl`	Multiple Kernel Sparse Representations for Supervised and Unsupervised Learning CoRR Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2013	J	`jnl`	Recovering Non-negative and Combined Sparse Representations CoRR Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias
2013	—	`—`	Sparse Methods in Image Understanding and Computer Vision. Jayaraman J. Thiagarajan
2012	C	`conf`	Automated tumor segmentation using kernel sparse representations. BIBE Jayaraman J. Thiagarajan, Deepta Rajan, Karthikeyan Natesan Ramamurthy, David H. Frakes, Andreas Spanias
2012	—	`conf`	Implementation of a fast image coding and retrieval system using a GPU. ESPA Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2012	Misc	`conf`	Interactive DSP laboratories on mobile phones and tablets. ICASSP Jinru Liu, Shuang Hu, Jayaraman J. Thiagarajan, Xue Zhang, Suhas Ranganath, Mahesh K. Banavar, Andreas Spanias
2012	—	`conf`	Learning Multilevel Dictionaries for Compressed Sensing Using Discriminative Clustering. IIH-MSP Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias, Panos Nasiopoulos
2012	—	`conf`	Learning dictionaries with graph embedding constraints. ACSCC Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2012	B	`conf`	Supervised local sparse coding of sub-image features for image retrieval. ICIP Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias
2012	C	`conf`	Work in progress: Performing signal analysis laboratories using Android devices. FIE Suhas Ranganath, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Mahesh K. Banavar, Andreas Spanias
2011	—	`book`	Analysis of the MPEG-1 Layer III (MP3) Algorithm Using MATLAB Jayaraman J. Thiagarajan, Andreas Spanias
2011	—	`conf`	Analyte detection using an ion-channel sensor array. DSP Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Michael Goryll, Andreas Spanias, Trevor Thornton
2011	B	`conf`	Improved sparse coding using manifold projections. ICIP Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias
2011	—	`conf`	Learning dictionaries for local sparse coding in image classification. ACSCC Jayaraman J. Thiagarajan, Andreas Spanias
2011	J	`jnl`	Optimality and stability of the K-hyperline clustering algorithm. Pattern Recognit. Lett. Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2011	J	`jnl`	Transform domain features for ion-channel signal classification. Biomed. Signal Process. Control. Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Michael Goryll, Andreas Spanias, Trevor Thornton, Stephen M. Phillips
2011	C	`conf`	Work in progress - Interactive signal-processing labs and simulations on iOS devices. FIE Jinru Liu, Andreas Spanias, Mahesh K. Banavar, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Shuang Hu, Xue Zhang
2011	C	`conf`	Work in progress - Modules and laboratories for a pathways course in signals and systems. FIE Kostas Tsakalis, Jayaraman J. Thiagarajan, Tolga M. Duman, Martin Reisslein, G. Tong Zhou, Xiaoli Ma, Photini Spanias
2010	Misc	`conf`	Dimensionality Reduction for Distance Based Video Clustering. AIAI Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2009	B	`conf`	Fast image registration with non-stationary Gauss-Markov random field templates. ICIP Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias
2009	—	`conf`	Template Learning using Wavelet Domain Statistical Models. SGAI Conf. Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias
2008	—	`conf`	Sparse Representations for Pattern Classification using Learned Dictionaries. SGAI Conf. Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias