29 citations · 36 across the 10 of their papers we have counts for
5 papers · 1 filter
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions
Kwan Ho Ryan Chan, Aditya Chattopadhyay, Benjamin David Haeffele +1
Variational Information Pursuit (V-IP) is a framework for making interpretable predictions by design by sequentially selecting a short chain of task-relevant, user-defined and inte…
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
Hancheng Min, Enrique Mallada, René Vidal
This paper studies the problem of training a two-layer ReLU network for binary classification using gradient flow with small initialization. We consider a training dataset with wel…
The Ideal Continual Learner: An Agent That Never Forgets
Liangzu Peng, Paris V. Giampouras, René Vidal
The goal of continual learning is to find a model that solves multiple learning tasks which are presented sequentially to the learner. A key challenge in this setting is that the l…
A Linearly Convergent GAN Inversion-based Algorithm for Reverse Engineering of Deceptions
Darshan Thaker, Paris Giampouras, René Vidal
An important aspect of developing reliable deep learning systems is devising strategies that make these systems robust to adversarial attacks. There is a long line of work that foc…
Convergence and Implicit Bias of Gradient Flow on Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal +1
Neural networks trained via gradient descent with random initialization and without any regularization enjoy good generalization performance in practice despite being highly overpa…