Jeremias Sulam

96 papers A* 14A 1B 1Misc 2Journal 68Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Global Sequential Testing for Multi-Stream Auditing. CoRR Beepul Bharti, Ambar Pal, Jeremias Sulam
2025	J	`jnl`	Aligning Explanations with Human Communication. CoRR Jacopo Teneggi, Zhenzhen Wang, Paul H. Yi, Tianmin Shu, Jeremias Sulam
2025	J	`jnl`	Beyond Scores: Proximal Diffusion Models. CoRR Zhenghan Fang, Mateo Díaz, Sam Buchanan, Jeremias Sulam
2025	J	`jnl`	Bi-level graph learning unveils prognosis-relevant tumor microenvironment patterns in breast multiplexed digital pathology. Patterns Zhenzhen Wang, Cesar A. Santa-Maria, Aleksander S. Popel, Jeremias Sulam
2025	—	`conf`	Concept Bottleneck Model with Zero Performance Loss. CPAL Zhenzhen Wang, Aleksander S. Popel, Jeremias Sulam
2025	—	`ed.`	Conference on Parsimony and Learning, Stanford University, USA, 24-27 March 2025. CPAL Beidi Chen, Shijia Liu, Mert Pilanci, Weijie Su, Jeremias Sulam, Yuxiang Wang, Zhihui Zhu
2025	—	`conf`	Conformal Risk Control for Semantic Uncertainty Quantification in Computed Tomography. MICCAI (14) Jacopo Teneggi, J. Webster Stayman, Jeremias Sulam
2025	J	`jnl`	Conformal Risk Control for Semantic Uncertainty Quantification in Computed Tomography. CoRR Jacopo Teneggi, J. Webster Stayman, Jeremias Sulam
2025	J	`jnl`	Disentangling Safe and Unsafe Corruptions via Anisotropy and Locality. CoRR Ramchandran Muthukumar, Ambar Pal, Jeremias Sulam, René Vidal
2025	A*	`conf`	Disentangling Safe and Unsafe Image Corruptions via Anisotropy and Locality. CVPR Ramchandran Muthukumar, Ambar Pal, Jeremias Sulam, René Vidal
2025	J	`jnl`	Fourier Diffusion Models: A Method to Control MTF and NPS in Score-Based Stochastic Image Generation. IEEE Trans. Medical Imaging Matthew Tivnan, Jacopo Teneggi, Tzu-Cheng Lee, Ruoqiao Zhang, Kirsten Boedeker, Liang Cai, Grace J. Gang, Jeremias Sulam, J. Webster Stayman
2025	J	`jnl`	Learning Regularization Functionals for Inverse Problems: A Comparative Study. CoRR Johannes Hertrich, Hok Shing Wong, Alexander Denker, Stanislas Ducotterd, Zhenghan Fang, Markus Haltmeier, Zeljko Kereta, Erich Kobler, Oscar Leong, Mohammad Sadegh Salehi, Carola-Bibiane Schönlieb, Johannes Schwab, Zakhar Shumaylov, Jeremias Sulam, German Shâma Wache, Martin Zach, Yasi Zhang, Matthias J. Ehrhardt, Sebastian Neumayer
2025	A*	`conf`	Multiaccuracy and Multicalibration via Proxy Groups. ICML Beepul Bharti, Mary Versa Clemens-Sewall, Paul H. Yi, Jeremias Sulam
2025	J	`jnl`	Multiaccuracy and Multicalibration via Proxy Groups. CoRR Beepul Bharti, Mary Versa Clemens-Sewall, Paul H. Yi, Jeremias Sulam
2025	J	`jnl`	ProxT2I: Efficient Reward-Guided Text-to-Image Generation via Proximal Diffusion. CoRR Zhenghan Fang, Jian Zheng, Qiaozi Gao, Xiaofeng Gao, Jeremias Sulam
2025	—	`conf`	Sufficient and Necessary Explanations (and What Lies in Between). CPAL Beepul Bharti, Paul H. Yi, Jeremias Sulam
2024	J	`jnl`	Certified Robustness against Sparse Adversarial Perturbations via Data Localization. CoRR Ambar Pal, René Vidal, Jeremias Sulam
2024	J	`jnl`	Certified Robustness against Sparse Adversarial Perturbations via Data Localization. Trans. Mach. Learn. Res. Ambar Pal, René Vidal, Jeremias Sulam
2024	J	`jnl`	Gradient-Based Saliency Maps Are Not Trustworthy Visual Explanations of Automated AI Musculoskeletal Diagnoses. J. Imaging Inform. Medicine Kesavan Venkatesh, Simukayi Mutasa, Fletcher Moore, Jeremias Sulam, Paul H. Yi
2024	J	`jnl`	I Bet You Did Not Mean That: Testing Semantic Importance via Betting. CoRR Jacopo Teneggi, Jeremias Sulam
2024	J	`jnl`	Pivotal Auto-Encoder via Self-Normalizing ReLU. CoRR Nelson Goldenstein, Jeremias Sulam, Yaniv Romano
2024	J	`jnl`	Pivotal Auto-Encoder via Self-Normalizing ReLU. IEEE Trans. Signal Process. Nelson Goldenstein, Jeremias Sulam, Yaniv Romano
2024	—	`conf`	ProxiMO: Proximal Multi-operator Networks for Quantitative Susceptibility Mapping. MLCN@MICCAI Shmuel Orenstein, Zhenghan Fang, Hyeong-Geol Shin, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2024	J	`jnl`	Sufficient and Necessary Explanations (and What Lies in Between). CoRR Beepul Bharti, Paul H. Yi, Jeremias Sulam
2024	A*	`conf`	Testing Semantic Importance via Betting. NeurIPS Jacopo Teneggi, Jeremias Sulam
2024	A*	`conf`	What's in a Prior? Learned Proximal Networks for Inverse Problems. ICLR Zhenghan Fang, Sam Buchanan, Jeremias Sulam
2023	A*	`conf`	Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness. NeurIPS Ambar Pal, Jeremias Sulam, René Vidal
2023	J	`jnl`	Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness. CoRR Ambar Pal, Jeremias Sulam, René Vidal
2023	J	`jnl`	Adversarial Robustness of Sparse Local Lipschitz Predictors. SIAM J. Math. Data Sci. Ramchandran Muthukumar, Jeremias Sulam
2023	J	`jnl`	DeepSTI: Towards tensor reconstruction using fewer orientations in susceptibility tensor imaging. Medical Image Anal. Zhenghan Fang, Kuo-Wei Lai, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2023	J	`jnl`	Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R NeuroImage Peter van Gelderen, Xu Li, Jacco A. de Zwart, Erin S. Beck, Serhat V. Okar, Yujia Huang, KuoWei Lai, Jeremias Sulam, Peter C. M. van Zijl, Daniel S. Reich, Jeff H. Duyn, Jiaen Liu
2023	A*	`conf`	Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors. NeurIPS Beepul Bharti, Paul H. Yi, Jeremias Sulam
2023	J	`jnl`	Fast Hierarchical Games for Image Explanations. IEEE Trans. Pattern Anal. Mach. Intell. Jacopo Teneggi, Alexandre Luster, Jeremias Sulam
2023	A*	`conf`	How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control. ICML Jacopo Teneggi, Matthew Tivnan, J. Webster Stayman, Jeremias Sulam
2023	J	`jnl`	How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control. CoRR Jacopo Teneggi, Matthew Tivnan, J. Webster Stayman, Jeremias Sulam
2023	J	`jnl`	SHAP-XRT: The Shapley Value Meets Conditional Independence Testing. Trans. Mach. Learn. Res. Jacopo Teneggi, Beepul Bharti, Yaniv Romano, Jeremias Sulam
2023	A*	`conf`	Sparsity-aware generalization theory for deep neural networks. COLT Ramchandran Muthukumar, Jeremias Sulam
2023	J	`jnl`	Sparsity-aware generalization theory for deep neural networks. CoRR Ramchandran Muthukumar, Jeremias Sulam
2023	J	`jnl`	Understanding Noise-Augmented Training for Randomized Smoothing. CoRR Ambar Pal, Jeremias Sulam
2023	J	`jnl`	Understanding Noise-Augmented Training for Randomized Smoothing. Trans. Mach. Learn. Res. Ambar Pal, Jeremias Sulam
2023	—	`conf`	WaveSep: A Flexible Wavelet-Based Approach for Source Separation in Susceptibility Imaging. MLCN@MICCAI Zhenghan Fang, Hyeong-Geol Shin, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2023	J	`jnl`	What's in a Prior? Learned Proximal Networks for Inverse Problems. CoRR Zhenghan Fang, Sam Buchanan, Jeremias Sulam
2022	J	`jnl`	Adversarial robustness of sparse local Lipschitz predictors. CoRR Ramchandran Muthukumar, Jeremias Sulam
2022	J	`jnl`	Antibody structure prediction using interpretable deep learning. Patterns Jeffrey A. Ruffolo, Jeremias Sulam, Jeffrey J. Gray
2022	J	`jnl`	DeepSTI: Towards Tensor Reconstruction using Fewer Orientations in Susceptibility Tensor Imaging. CoRR Zhenghan Fang, Kuo-Wei Lai, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2022	A	`conf`	Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms. AISTATS Joshua Agterberg, Jeremias Sulam
2022	J	`jnl`	Estimating and Controlling for Fairness via Sensitive Attribute Predictors. CoRR Beepul Bharti, Paul H. Yi, Jeremias Sulam
2022	J	`jnl`	From Shapley back to Pearson: Hypothesis Testing via the Shapley Value. CoRR Jacopo Teneggi, Beepul Bharti, Yaniv Romano, Jeremias Sulam
2022	J	`jnl`	Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images. IEEE Trans. Medical Imaging Zhenzhen Wang, Carla Saoud, Sintawat Wangsiricharoen, Aaron W. James, Aleksander S. Popel, Jeremias Sulam
2022	J	`jnl`	Prospective Learning: Back to the Future. CoRR Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam S. Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
2022	J	`jnl`	Recovery and Generalization in Over-Realized Dictionary Learning. J. Mach. Learn. Res. Jeremias Sulam, Chong You, Zhihui Zhu
2022	J	`jnl`	Weakly Supervised Learning Significantly Reduces the Number of Labels Required for Intracranial Hemorrhage Detection on Head CT. CoRR Jacopo Teneggi, Paul H. Yi, Jeremias Sulam
2021	A*	`conf`	A Geometric Analysis of Neural Collapse with Unconstrained Features. NeurIPS Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
2021	J	`jnl`	A Geometric Analysis of Neural Collapse with Unconstrained Features. CoRR Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu
2021	J	`jnl`	Deciphering antibody affinity maturation with language models and weakly supervised learning. CoRR Jeffrey A. Ruffolo, Jeffrey J. Gray, Jeremias Sulam
2021	J	`jnl`	Fast Hierarchical Games for Image Explanations. CoRR Jacopo Teneggi, Alexandre Luster, Jeremias Sulam
2021	J	`jnl`	Label Cleaning Multiple Instance Learning: Refining Coarse Annotations on Single Whole-Slide Images. CoRR Zhenzhen Wang, Aleksander S. Popel, Jeremias Sulam
2020	J	`jnl`	Adversarial Noise Attacks of Deep Learning Architectures: Stability Analysis via Sparse-Modeled Signals. J. Math. Imaging Vis. Yaniv Romano, Aviad Aberdam, Jeremias Sulam, Michael Elad
2020	A*	`conf`	Adversarial Robustness of Supervised Sparse Coding. NeurIPS Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
2020	J	`jnl`	Adversarial Robustness of Supervised Sparse Coding. CoRR Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
2020	A*	`conf`	Conformal Symplectic and Relativistic Optimization. NeurIPS Guilherme França, Jeremias Sulam, Daniel P. Robinson, René Vidal
2020	J	`jnl`	Deep Learning in Protein Structural Modeling and Design. CoRR Wenhao Gao, Sai Pooja Mahajan, Jeremias Sulam, Jeffrey J. Gray
2020	J	`jnl`	Deep Learning in Protein Structural Modeling and Design. Patterns Wenhao Gao, Sai Pooja Mahajan, Jeremias Sulam, Jeffrey J. Gray
2020	J	`jnl`	Geometric potentials from deep learning improve prediction of CDR H3 loop structures. Bioinform. Jeffrey A. Ruffolo, Carlos Guerra, Sai Pooja Mahajan, Jeremias Sulam, Jeffrey J. Gray
2020	—	`conf`	Learned Proximal Networks for Quantitative Susceptibility Mapping. MICCAI (2) Kuo-Wei Lai, Manisha Aggarwal, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2020	J	`jnl`	Learned Proximal Networks for Quantitative Susceptibility Mapping. CoRR Kuo-Wei Lai, Manisha Aggarwal, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2020	A*	`conf`	Learning to solve TV regularised problems with unrolled algorithms. NeurIPS Hamza Cherkaoui, Jeremias Sulam, Thomas Moreau
2020	J	`jnl`	On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Jeremias Sulam, Aviad Aberdam, Amir Beck, Michael Elad
2020	J	`jnl`	Recovery and Generalization in Over-Realized Dictionary Learning. CoRR Jeremias Sulam, Chong You, Zhihui Zhu
2020	J	`jnl`	Variations on the Convolutional Sparse Coding Model. IEEE Trans. Signal Process. Ives Rey-Otero, Jeremias Sulam, Michael Elad
2019	A*	`conf`	A Local Block Coordinate Descent Algorithm for the CSC Model. CVPR Ev Zisselman, Jeremias Sulam, Michael Elad
2019	J	`jnl`	MMSE Approximation For Sparse Coding Algorithms Using Stochastic Resonance. IEEE Trans. Signal Process. Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad
2019	J	`jnl`	Multi-Layer Sparse Coding: The Holistic Way. SIAM J. Math. Data Sci. Aviad Aberdam, Jeremias Sulam, Michael Elad
2018	J	`jnl`	A Local Block Coordinate Descent Algorithm for the Convolutional Sparse Coding Model. CoRR Ev Zisselman, Jeremias Sulam, Michael Elad
2018	—	`—`	From Local to Global Sparse Modeling. Jeremias Sulam
2018	J	`jnl`	Improving Pursuit Algorithms Using Stochastic Resonance. CoRR Dror Simon, Jeremias Sulam, Yaniv Romano, Yue M. Lu, Michael Elad
2018	J	`jnl`	Multi Layer Sparse Coding: the Holistic Way. CoRR Aviad Aberdam, Jeremias Sulam, Michael Elad
2018	J	`jnl`	Multilayer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. IEEE Trans. Signal Process. Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad
2018	J	`jnl`	On Multi-Layer Basis Pursuit, Efficient Algorithms and Convolutional Neural Networks. CoRR Jeremias Sulam, Aviad Aberdam, Michael Elad
2018	Misc	`conf`	Projecting on to the Multi-Layer Convolutional Sparse Coding Model. ICASSP Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad
2018	J	`jnl`	Theoretical Foundations of Deep Learning via Sparse Representations: A Multilayer Sparse Model and Its Connection to Convolutional Neural Networks. IEEE Signal Process. Mag. Vardan Papyan, Yaniv Romano, Jeremias Sulam, Michael Elad
2017	A*	`conf`	Convolutional Dictionary Learning via Local Processing. ICCV Vardan Papyan, Yaniv Romano, Michael Elad, Jeremias Sulam
2017	J	`jnl`	Convolutional Dictionary Learning via Local Processing. CoRR Vardan Papyan, Yaniv Romano, Jeremias Sulam, Michael Elad
2017	J	`jnl`	Dynamical system classification with diffusion embedding for ECG-based person identification. Signal Process. Jeremias Sulam, Yaniv Romano, Ronen Talmon
2017	—	`conf`	Maximizing AUC with Deep Learning for Classification of Imbalanced Mammogram Datasets. VCBM Jeremias Sulam, Rami Ben-Ari, Pavel Kisilev
2017	J	`jnl`	Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning. CoRR Jeremias Sulam, Vardan Papyan, Yaniv Romano, Michael Elad
2017	J	`jnl`	Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding. CoRR Vardan Papyan, Jeremias Sulam, Michael Elad
2017	J	`jnl`	Working Locally Thinking Globally: Theoretical Guarantees for Convolutional Sparse Coding. IEEE Trans. Signal Process. Vardan Papyan, Jeremias Sulam, Michael Elad
2016	J	`jnl`	Large Inpainting of Face Images With Trainlets. IEEE Signal Process. Lett. Jeremias Sulam, Michael Elad
2016	J	`jnl`	Trainlets: Dictionary Learning in High Dimensions. CoRR Jeremias Sulam, Boaz Ophir, Michael Zibulevsky, Michael Elad
2016	J	`jnl`	Trainlets: Dictionary Learning in High Dimensions. IEEE Trans. Signal Process. Jeremias Sulam, Boaz Ophir, Michael Zibulevsky, Michael Elad
2016	J	`jnl`	Working Locally Thinking Globally - Part I: Theoretical Guarantees for Convolutional Sparse Coding. CoRR Vardan Papyan, Jeremias Sulam, Michael Elad
2016	J	`jnl`	Working Locally Thinking Globally - Part II: Stability and Algorithms for Convolutional Sparse Coding. CoRR Vardan Papyan, Jeremias Sulam, Michael Elad
2015	Misc	`conf`	Fusion of ultrasound harmonic imaging with clutter removal using sparse signal separation. ICASSP Javier S. Turek, Jeremias Sulam, Michael Elad, Irad Yavneh
2014	—	`conf`	Expected Patch Log Likelihood with a Sparse Prior. EMMCVPR Jeremias Sulam, Michael Elad
2014	B	`conf`	Image denoising through multi-scale learnt dictionaries. ICIP Jeremias Sulam, Boaz Ophir, Michael Elad