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On the Cryptographic Hardness of Learning Single Periodic Neurons


Jun 20, 2021
Min Jae Song, Ilias Zadik, Joan Bruna

* 54 pages 

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Offline RL Without Off-Policy Evaluation


Jun 16, 2021
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna


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On the Sample Complexity of Learning with Geometric Stability


Jun 14, 2021
Alberto Bietti, Luca Venturi, Joan Bruna


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On Energy-Based Models with Overparametrized Shallow Neural Networks


May 05, 2021
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna


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Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges


May 02, 2021
Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Veličković

* 156 pages. Work in progress -- comments welcome! 

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Symmetry Breaking in Symmetric Tensor Decomposition


Mar 10, 2021
Yossi Arjevani, Joan Bruna, Michael Field, Joe Kileel, Matthew Trager, Francis Williams


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Depth separation beyond radial functions


Feb 03, 2021
Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna


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Self-Supervised Equivariant Scene Synthesis from Video


Feb 01, 2021
Cinjon Resnick, Or Litany, Cosmas Heiß, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

* arXiv admin note: text overlap with arXiv:2011.05787 

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Learned Equivariant Rendering without Transformation Supervision


Nov 11, 2020
Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

* Workshop on Differentiable Vision, Graphics, and Physics in Machine Learning at NeurIPS 2020 

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On Graph Neural Networks versus Graph-Augmented MLPs


Oct 28, 2020
Lei Chen, Zhengdao Chen, Joan Bruna


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Kernel-Based Smoothness Analysis of Residual Networks


Sep 21, 2020
Tom Tirer, Joan Bruna, Raja Giryes


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A Dynamical Central Limit Theorem for Shallow Neural Networks


Aug 21, 2020
Zhengdao Chen, Grant M. Rotskoff, Joan Bruna, Eric Vanden-Eijnden


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A Functional Perspective on Learning Symmetric Functions with Neural Networks


Aug 16, 2020
Aaron Zweig, Joan Bruna


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Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems


Jul 28, 2020
Donsub Rim, Luca Venturi, Joan Bruna, Benjamin Peherstorfer


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In-Distribution Interpretability for Challenging Modalities


Jul 07, 2020
Cosmas Heiß, Ron Levie, Cinjon Resnick, Gitta Kutyniok, Joan Bruna


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Overfitting and Optimization in Offline Policy Learning


Jun 27, 2020
David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna


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Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks


Jun 24, 2020
Francis Williams, Matthew Trager, Joan Bruna, Denis Zorin


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On Sparsity in Overparametrised Shallow ReLU Networks


Jun 18, 2020
Jaume de Dios, Joan Bruna

* submitted to Neurips'20 

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IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method


Jun 11, 2020
Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin


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Continuous LWE


May 19, 2020
Joan Bruna, Oded Regev, Min Jae Song, Yi Tang

* 28 pages 

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A Permutation-Equivariant Neural Network Architecture For Auction Design


Mar 02, 2020
Jad Rahme, Samy Jelassi, Joan Bruna, S. Matthew Weinberg


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Provably Efficient Third-Person Imitation from Offline Observation


Feb 27, 2020
Aaron Zweig, Joan Bruna


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Can graph neural networks count substructures?


Feb 27, 2020
Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna


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A mean-field analysis of two-player zero-sum games


Feb 24, 2020
Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant Rotskoff, Joan Bruna


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