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Jeremias Sulam

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What's in a Prior? Learned Proximal Networks for Inverse Problems

Oct 22, 2023
Zhenghan Fang, Sam Buchanan, Jeremias Sulam

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Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness

Sep 28, 2023
Ambar Pal, Jeremias Sulam, René Vidal

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Sparsity-aware generalization theory for deep neural networks

Jul 04, 2023
Ramchandran Muthukumar, Jeremias Sulam

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Understanding Noise-Augmented Training for Randomized Smoothing

May 08, 2023
Ambar Pal, Jeremias Sulam

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How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control

Feb 07, 2023
Jacopo Teneggi, Matt Tivnan, J Webster Stayman, Jeremias Sulam

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Weakly Supervised Learning Significantly Reduces the Number of Labels Required for Intracranial Hemorrhage Detection on Head CT

Nov 29, 2022
Jacopo Teneggi, Paul H. Yi, Jeremias Sulam

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DeepSTI: Towards Tensor Reconstruction using Fewer Orientations in Susceptibility Tensor Imaging

Sep 09, 2022
Zhenghan Fang, Kuo-Wei Lai, Peter van Zijl, Xu Li, Jeremias Sulam

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Estimating and Controlling for Fairness via Sensitive Attribute Predictors

Jul 25, 2022
Beepul Bharti, Paul Yi, Jeremias Sulam

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From Shapley back to Pearson: Hypothesis Testing via the Shapley Value

Jul 14, 2022
Jacopo Teneggi, Beepul Bharti, Yaniv Romano, Jeremias Sulam

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Adversarial robustness of sparse local Lipschitz predictors

Feb 26, 2022
Ramchandran Muthukumar, Jeremias Sulam

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