289 citations · 1.7k across the 90 of their papers we have counts for
4 papers · 2 filters
Spectral Geometric Matrix Completion
Amit Boyarski, Sanketh Vedula, Alex Bronstein
Deep Matrix Factorization (DMF) is an emerging approach to the problem of matrix completion. Recent works have established that gradient descent applied to a DMF model induces an i…
Smoothed Inference for Adversarially-Trained Models
Yaniv Nemcovsky, Evgenii Zheltonozhskii, Chaim Baskin +4
Deep neural networks are known to be vulnerable to adversarial attacks. Current methods of defense from such attacks are based on either implicit or explicit regularization, e.g.,…
Loss Aware Post-training Quantization
Yury Nahshan, Brian Chmiel, Chaim Baskin +4
Neural network quantization enables the deployment of large models on resource-constrained devices. Current post-training quantization methods fall short in terms of accuracy for I…
Horizontal Flows and Manifold Stochastics in Geometric Deep Learning
Stefan Sommer, Alex Bronstein
We introduce two constructions in geometric deep learning for 1) transporting orientation-dependent convolutional filters over a manifold in a continuous way and thereby defining a…