97 citations · 117 across the 5 of their papers we have counts for
5 papers
Understanding Noise-Augmented Training for Randomized Smoothing
Ambar Pal, Jeremias Sulam
Randomized smoothing is a technique for providing provable robustness guarantees against adversarial attacks while making minimal assumptions about a classifier. This method relies…
Fourier Diffusion Models: A Method to Control MTF and NPS in Score-Based Stochastic Image Generation
Matthew Tivnan, Jacopo Teneggi, Tzu-Cheng Lee +6
Score-based stochastic denoising models have recently been demonstrated as powerful machine learning tools for conditional and unconditional image generation. The existing methods…
Deciphering antibody affinity maturation with language models and weakly supervised learning
Jeffrey A. Ruffolo, Jeffrey J. Gray, Jeremias Sulam
In response to pathogens, the adaptive immune system generates specific antibodies that bind and neutralize foreign antigens. Understanding the composition of an individual's immun…
Working Locally Thinking Globally - Part II: Stability and Algorithms for Convolutional Sparse Coding
Vardan Papyan, Jeremias Sulam, Michael Elad
The convolutional sparse model has recently gained increasing attention in the signal and image processing communities, and several methods have been proposed for solving the pursu…
Working Locally Thinking Globally - Part I: Theoretical Guarantees for Convolutional Sparse Coding
Vardan Papyan, Jeremias Sulam, Michael Elad
The celebrated sparse representation model has led to remarkable results in various signal processing tasks in the last decade. However, despite its initial purpose of serving as a…