12 citations · 46 across the 8 of their papers we have counts for
11 papers
On Energy-Based Models with Overparametrized Shallow Neural Networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden +1
Energy-based models (EBMs) are a simple yet powerful framework for generative modeling. They are based on a trainable energy function which defines an associated Gibbs measure, and…
Depth separation beyond radial functions
Luca Venturi, Samy Jelassi, Tristan Ozuch +1
High-dimensional depth separation results for neural networks show that certain functions can be efficiently approximated by two-hidden-layer networks but not by one-hidden-layer o…
Self-Supervised Equivariant Scene Synthesis from Video
Cinjon Resnick, Or Litany, Cosmas Heiß +3
We propose a self-supervised framework to learn scene representations from video that are automatically delineated into background, characters, and their animations. Our method cap…
On Graph Neural Networks versus Graph-Augmented MLPs
Lei Chen, Zhengdao Chen, Joan Bruna
From the perspective of expressive power, this work compares multi-layer Graph Neural Networks (GNNs) with a simplified alternative that we call Graph-Augmented Multi-Layer Percept…
Learned Equivariant Rendering without Transformation Supervision
Cinjon Resnick, Or Litany, Hugo Larochelle +2
We propose a self-supervised framework to learn scene representations from video that are automatically delineated into objects and background. Our method relies on moving objects…
Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks
Pau Batlle, Joan Bruna, Carlos Fernandez-Granda +1
We present a general framework for adaptive allocation of viral tests in social contact networks. We pose and solve several complementary problems. First, we consider the design of…