Sulam, Jeremias

23 publications

NeurIPS 2025 Beyond Scores: Proximal Diffusion Models Zhenghan Fang, Mateo Diaz Diaz, Sam Buchanan, Jeremias Sulam

CPAL 2025 Concept Bottleneck Model with Zero Performance Loss Zhenzhen Wang, Aleksander Popel, Jeremias Sulam

CVPR 2025 Disentangling Safe and Unsafe Image Corruptions via Anisotropy and Locality Ramchandran Muthukumar, Ambar Pal, Jeremias Sulam, Rene Vidal

ICML 2025 Multiaccuracy and Multicalibration via Proxy Groups Beepul Bharti, Mary Versa Clemens-Sewall, Paul Yi, Jeremias Sulam

CPAL 2025 Sufficient and Necessary Explanations (and What Lies in Between) Beepul Bharti, Paul Yi, Jeremias Sulam

TMLR 2024 Certified Robustness Against Sparse Adversarial Perturbations via Data Localization Ambar Pal, Rene Vidal, Jeremias Sulam

NeurIPS 2024 Testing Semantic Importance via Betting Jacopo Teneggi, Jeremias Sulam

ICLR 2024 What's in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang, Sam Buchanan, Jeremias Sulam

NeurIPS 2023 Adversarial Examples Might Be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal, Jeremias Sulam, Rene Vidal

NeurIPSW 2023 Bi-Level Graphs for Cellular Pattern Discovery Zhenzhen Wang, Aleksander S. Popel, Jeremias Sulam

NeurIPS 2023 Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors Beepul Bharti, Paul Yi, Jeremias Sulam

ICML 2023 How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control Jacopo Teneggi, Matthew Tivnan, Web Stayman, Jeremias Sulam

TMLR 2023 SHAP-XRT: The Shapley Value Meets Conditional Independence Testing Jacopo Teneggi, Beepul Bharti, Yaniv Romano, Jeremias Sulam

COLT 2023 Sparsity-Aware Generalization Theory for Deep Neural Networks Ramchandran Muthukumar, Jeremias Sulam

TMLR 2023 Understanding Noise-Augmented Training for Randomized Smoothing Ambar Pal, Jeremias Sulam

NeurIPSW 2023 What’s in a Prior? Learned Proximal Networks for Inverse Problems Zhenghan Fang, Sam Buchanan, Jeremias Sulam

AISTATS 2022 Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms Joshua Agterberg, Jeremias Sulam

JMLR 2022 Recovery and Generalization in Over-Realized Dictionary Learning Jeremias Sulam, Chong You, Zhihui Zhu

NeurIPS 2021 A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu

NeurIPS 2020 Adversarial Robustness of Supervised Sparse Coding Jeremias Sulam, Ramchandran Muthukumar, Raman Arora

NeurIPS 2020 Conformal Symplectic and Relativistic Optimization Guilherme Franca, Jeremias Sulam, Daniel Robinson, Rene Vidal

NeurIPS 2020 Learning to Solve TV Regularised Problems with Unrolled Algorithms Hamza Cherkaoui, Jeremias Sulam, Thomas Moreau

ICCV 2017 Convolutional Dictionary Learning via Local Processing Vardan Papyan, Yaniv Romano, Jeremias Sulam, Michael Elad