Joan Bruna - RankMe

196 papers A* 50A 1B 1C 1Misc 3Journal 119Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Towards Infinitely Long Neural Simulations: Self-Refining Neural Surrogate Models for Dynamical Systems. CoRR Qi Liu, Laure Zanna, Joan Bruna
2025	J	`jnl`	Axial Neural Networks for Dimension-Free Foundation Models. CoRR Hyunsu Kim, Jonggeon Park, Joan Bruna, Hongseok Yang, Juho Lee
2025	J	`jnl`	Compositional Reasoning with Transformers, RNNs, and Chain of Thought. CoRR Gilad Yehudai, Noah Amsel, Joan Bruna
2025	J	`jnl`	Data-driven multiscale modeling for correcting dynamical systems. Mach. Learn. Sci. Technol. Karl Otness, Laure Zanna, Joan Bruna
2025	A*	`conf`	Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers. ICLR Lei Chen, Joan Bruna, Alberto Bietti
2025	J	`jnl`	Emergence of Linear Truth Encodings in Language Models. CoRR Shauli Ravfogel, Gilad Yehudai, Tal Linzen, Joan Bruna, Alberto Bietti
2025	J	`jnl`	Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants. CoRR Chirag Modi, Jiequn Han, Eric Vanden-Eijnden, Joan Bruna
2025	J	`jnl`	Geometry and Optimization of Shallow Polynomial Networks. CoRR Yossi Arjevani, Joan Bruna, Joe Kileel, Elzbieta Polak, Matthew Trager
2025	A*	`conf`	Mean-field analysis of polynomial-width two-layer neural network beyond finite time horizon. COLT Margalit Glasgow, Denny Wu, Joan Bruna
2025	J	`jnl`	Propagation of Chaos in One-hidden-layer Neural Networks beyond Logarithmic Time. CoRR Margalit Glasgow, Denny Wu, Joan Bruna
2025	A*	`conf`	Quality over Quantity in Attention Layers: When Adding More Heads Hurts. ICLR Noah Amsel, Gilad Yehudai, Joan Bruna
2025	J	`jnl`	Survey on Algorithms for multi-index models. CoRR Joan Bruna, Daniel Hsu
2025	J	`jnl`	The Generative Leap: Sharp Sample Complexity for Efficiently Learning Gaussian Multi-Index Models. CoRR Alex Damian, Jason D. Lee, Joan Bruna
2025	A*	`conf`	Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos. ICML Christian Pedersen, Laure Zanna, Joan Bruna
2025	J	`jnl`	Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos. CoRR Christian Pedersen, Laure Zanna, Joan Bruna
2024	A*	`conf`	Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract). COLT Alex Damian, Loucas Pillaud-Vivien, Jason D. Lee, Joan Bruna
2024	J	`jnl`	Computational-Statistical Gaps in Gaussian Single-Index Models. CoRR Alex Damian, Loucas Pillaud-Vivien, Jason D. Lee, Joan Bruna
2024	J	`jnl`	How Truncating Weights Improves Reasoning in Language Models. CoRR Lei Chen, Joan Bruna, Alberto Bietti
2024	J	`jnl`	Neural Galerkin schemes with active learning for high-dimensional evolution equations. J. Comput. Phys. Joan Bruna, Benjamin Peherstorfer, Eric Vanden-Eijnden
2024	J	`jnl`	On the Benefits of Rank in Attention Layers. CoRR Noah Amsel, Gilad Yehudai, Joan Bruna
2024	J	`jnl`	Posterior Sampling with Denoising Oracles via Tilted Transport. CoRR Joan Bruna, Jiequn Han
2024	A*	`conf`	Provable Posterior Sampling with Denoising Oracles via Tilted Transport. NeurIPS Joan Bruna, Jiequn Han
2024	A*	`conf`	Stochastic Optimal Control Matching. NeurIPS Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen
2024	A*	`conf`	Symmetric Single Index Learning. ICLR Aaron Zweig, Joan Bruna
2023	A*	`conf`	A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks. NeurIPS Vignesh Kothapalli, Tom Tirer, Joan Bruna
2023	J	`jnl`	A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks. CoRR Vignesh Kothapalli, Tom Tirer, Joan Bruna
2023	A*	`conf`	Beyond the Edge of Stability via Two-step Gradient Updates. ICML Lei Chen, Joan Bruna
2023	A*	`conf`	Conditionally Strongly Log-Concave Generative Models. ICML Florentin Guth, Etienne Lempereur, Joan Bruna, Stéphane Mallat
2023	J	`jnl`	Conditionally Strongly Log-Concave Generative Models. CoRR Florentin Guth, Etienne Lempereur, Joan Bruna, Stéphane Mallat
2023	J	`jnl`	Data-driven multiscale modeling of subgrid parameterizations in climate models. CoRR Karl Otness, Laure Zanna, Joan Bruna
2023	A*	`conf`	Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. NeurIPS David Brandfonbrener, Ofir Nachum, Joan Bruna
2023	J	`jnl`	Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation. CoRR David Brandfonbrener, Ofir Nachum, Joan Bruna
2023	J	`jnl`	On Learning Gaussian Multi-index Models with Gradient Flow. CoRR Alberto Bietti, Joan Bruna, Loucas Pillaud-Vivien
2023	J	`jnl`	On Single Index Models beyond Gaussian Data. CoRR Joan Bruna, Loucas Pillaud-Vivien, Aaron Zweig
2023	A*	`conf`	On Single-Index Models beyond Gaussian Data. NeurIPS Aaron Zweig, Loucas Pillaud-Vivien, Joan Bruna
2023	J	`jnl`	Stochastic Optimal Control Matching. CoRR Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen
2023	J	`jnl`	Symmetric Single Index Learning. CoRR Aaron Zweig, Joan Bruna
2022	J	`jnl`	A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks. CoRR Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna
2022	J	`jnl`	Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks. SIAM J. Control. Optim. Pau Batlle, Joan Bruna, Carlos Fernandez-Granda, Victor M. Preciado
2022	—	`conf`	Cartoon Explanations of Image Classifiers. ECCV (12) Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok
2022	J	`jnl`	Depth separation beyond radial functions. J. Mach. Learn. Res. Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna
2022	A*	`conf`	Exponential Separations in Symmetric Neural Networks. NeurIPS Aaron Zweig, Joan Bruna
2022	J	`jnl`	Exponential Separations in Symmetric Neural Networks. CoRR Aaron Zweig, Joan Bruna
2022	A*	`conf`	Extended Unconstrained Features Model for Exploring Deep Neural Collapse. ICML Tom Tirer, Joan Bruna
2022	J	`jnl`	Extended Unconstrained Features Model for Exploring Deep Neural Collapse. CoRR Tom Tirer, Joan Bruna
2022	J	`jnl`	Guest Editorial: Non-Euclidean Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori
2022	A*	`conf`	Lattice-Based Methods Surpass Sum-of-Squares in Clustering. COLT Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna
2022	J	`jnl`	Learning Single-Index Models with Shallow Neural Networks. CoRR Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song
2022	A*	`conf`	Learning single-index models with shallow neural networks. NeurIPS Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song
2022	A*	`conf`	Neural Fields as Learnable Kernels for 3D Reconstruction. CVPR Francis Williams, Zan Gojcic, Sameh Khamis, Denis Zorin, Joan Bruna, Sanja Fidler, Or Litany
2022	J	`jnl`	Neural Galerkin Scheme with Active Learning for High-Dimensional Evolution Equations. CoRR Joan Bruna, Benjamin Peherstorfer, Eric Vanden-Eijnden
2022	J	`jnl`	On Feature Learning in Neural Networks with Global Convergence Guarantees. CoRR Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna
2022	J	`jnl`	On Gradient Descent Convergence beyond the Edge of Stability. CoRR Lei Chen, Joan Bruna
2022	A*	`conf`	On Non-Linear operators for Geometric Deep Learning. NeurIPS Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon
2022	J	`jnl`	On Non-Linear operators for Geometric Deep Learning. CoRR Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon
2022	A*	`conf`	On feature learning in neural networks with global convergence guarantees. ICLR Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna
2022	J	`jnl`	Towards Antisymmetric Neural Ansatz Separation. CoRR Aaron Zweig, Joan Bruna
2022	A*	`conf`	When does return-conditioned supervised learning work for offline reinforcement learning? NeurIPS David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
2022	J	`jnl`	When does return-conditioned supervised learning work for offline reinforcement learning? CoRR David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna
2021	A*	`conf`	A Functional Perspective on Learning Symmetric Functions with Neural Networks. ICML Aaron Zweig, Joan Bruna
2021	A*	`conf`	A Permutation-Equivariant Neural Network Architecture For Auction Design. AAAI Jad Rahme, Samy Jelassi, Joan Bruna, S. Matthew Weinberg
2021	J	`jnl`	A Rate-Distortion Framework for Explaining Black-box Model Decisions. CoRR Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok
2021	—	`conf`	An Extensible Benchmark Suite for Learning to Simulate Physical Systems. NeurIPS Datasets and Benchmarks Karl Otness, Arvi Gjoka, Joan Bruna, Daniele Panozzo, Benjamin Peherstorfer, Teseo Schneider, Denis Zorin
2021	J	`jnl`	An Extensible Benchmark Suite for Learning to Simulate Physical Systems. CoRR Karl Otness, Arvi Gjoka, Joan Bruna, Daniele Panozzo, Benjamin Peherstorfer, Teseo Schneider, Denis Zorin
2021	J	`jnl`	Cartoon Explanations of Image Classifiers. CoRR Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok
2021	A*	`conf`	Continuous LWE. STOC Joan Bruna, Oded Regev, Min Jae Song, Yi Tang
2021	J	`jnl`	Depth separation beyond radial functions. CoRR Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna
2021	J	`jnl`	Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks. CoRR Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden
2021	J	`jnl`	Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges. CoRR Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Velickovic
2021	—	`conf`	Kernel-Based Smoothness Analysis of Residual Networks. MSML Tom Tirer, Joan Bruna, Raja Giryes
2021	J	`jnl`	Lattice-Based Methods Surpass Sum-of-Squares in Clustering. CoRR Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna
2021	Misc	`conf`	Learning the Relevant Substructures for Tasks on Graph Data. ICASSP Lei Chen, Zhengdao Chen, Joan Bruna
2021	—	`ed.`	Mathematical and Scientific Machine Learning, 16-19 August 2021, Virtual Conference / Lausanne, Switzerland. MSML Joan Bruna, Jan S. Hesthaven, Lenka Zdeborová
2021	J	`jnl`	Multi-fidelity Stability for Graph Representation Learning. CoRR Yihan He, Joan Bruna
2021	J	`jnl`	Neural Fields as Learnable Kernels for 3D Reconstruction. CoRR Francis Williams, Zan Gojcic, Sameh Khamis, Denis Zorin, Joan Bruna, Sanja Fidler, Or Litany
2021	A*	`conf`	Neural Splines: Fitting 3D Surfaces With Infinitely-Wide Neural Networks. CVPR Francis Williams, Matthew Trager, Joan Bruna, Denis Zorin
2021	A*	`conf`	Offline Contextual Bandits with Overparameterized Models. ICML David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2021	A*	`conf`	Offline RL Without Off-Policy Evaluation. NeurIPS David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
2021	J	`jnl`	Offline RL Without Off-Policy Evaluation. CoRR David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2021	A*	`conf`	On Energy-Based Models with Overparametrized Shallow Neural Networks. ICML Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
2021	J	`jnl`	On Energy-Based Models with Overparametrized Shallow Neural Networks. CoRR Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
2021	A*	`conf`	On Graph Neural Networks versus Graph-Augmented MLPs. ICLR Lei Chen, Zhengdao Chen, Joan Bruna
2021	A*	`conf`	On the Cryptographic Hardness of Learning Single Periodic Neurons. NeurIPS Min Jae Song, Ilias Zadik, Joan Bruna
2021	J	`jnl`	On the Cryptographic Hardness of Learning Single Periodic Neurons. CoRR Min Jae Song, Ilias Zadik, Joan Bruna
2021	A*	`conf`	On the Sample Complexity of Learning under Geometric Stability. NeurIPS Alberto Bietti, Luca Venturi, Joan Bruna
2021	J	`jnl`	On the Sample Complexity of Learning with Geometric Stability. CoRR Alberto Bietti, Luca Venturi, Joan Bruna
2021	J	`jnl`	Quantile Filtered Imitation Learning. CoRR David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2021	J	`jnl`	Self-Supervised Equivariant Scene Synthesis from Video. CoRR Cinjon Resnick, Or Litany, Cosmas Heiß, Hugo Larochelle, Joan Bruna, Kyunghyun Cho
2021	J	`jnl`	Symmetry Breaking in Symmetric Tensor Decomposition. CoRR Yossi Arjevani, Joan Bruna, Michael Field, Joe Kileel, Matthew Trager, Francis Williams
2020	A*	`conf`	A Dynamical Central Limit Theorem for Shallow Neural Networks. NeurIPS Zhengdao Chen, Grant M. Rotskoff, Joan Bruna, Eric Vanden-Eijnden
2020	J	`jnl`	A Dynamical Central Limit Theorem for Shallow Neural Networks. CoRR Zhengdao Chen, Grant M. Rotskoff, Joan Bruna, Eric Vanden-Eijnden
2020	J	`jnl`	A Functional Perspective on Learning Symmetric Functions with Neural Networks. CoRR Aaron Zweig, Joan Bruna
2020	J	`jnl`	A Permutation-Equivariant Neural Network Architecture For Auction Design. CoRR Jad Rahme, Samy Jelassi, Joan Bruna, S. Matthew Weinberg
2020	—	`conf`	A Rate-Distortion Framework for Explaining Black-Box Model Decisions. xxAI@ICML Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok
2020	A*	`conf`	A mean-field analysis of two-player zero-sum games. NeurIPS Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna
2020	J	`jnl`	A mean-field analysis of two-player zero-sum games. CoRR Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna
2020	J	`jnl`	Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks. CoRR Pau Batlle, Joan Bruna, Carlos Fernandez-Granda, Victor M. Preciado
2020	A*	`conf`	Can Graph Neural Networks Count Substructures? NeurIPS Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna
2020	J	`jnl`	Can graph neural networks count substructures? CoRR Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna
2020	J	`jnl`	Continuous LWE. CoRR Joan Bruna, Oded Regev, Min Jae Song, Yi Tang
2020	J	`jnl`	Continuous LWE. Electron. Colloquium Comput. Complex. Joan Bruna, Oded Regev, Min Jae Song, Yi Tang
2020	J	`jnl`	Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems. CoRR Donsub Rim, Luca Venturi, Joan Bruna, Benjamin Peherstorfer
2020	A*	`conf`	Extra-gradient with player sampling for faster convergence in n-player games. ICML Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna
2020	A*	`conf`	Geometric Insights into the Convergence of Nonlinear TD Learning. ICLR David Brandfonbrener, Joan Bruna
2020	A*	`conf`	IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. NeurIPS Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin
2020	J	`jnl`	IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. CoRR Yossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin
2020	J	`jnl`	In-Distribution Interpretability for Challenging Modalities. CoRR Cosmas Heiß, Ron Levie, Cinjon Resnick, Gitta Kutyniok, Joan Bruna
2020	J	`jnl`	Kernel-Based Smoothness Analysis of Residual Networks. CoRR Tom Tirer, Joan Bruna, Raja Giryes
2020	J	`jnl`	Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine Cella, Michael Eickenberg
2020	J	`jnl`	Learned Equivariant Rendering without Transformation Supervision. CoRR Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho
2020	J	`jnl`	Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks. CoRR Francis Williams, Matthew Trager, Joan Bruna, Denis Zorin
2020	J	`jnl`	On Graph Neural Networks versus Graph-Augmented MLPs. CoRR Lei Chen, Zhengdao Chen, Joan Bruna
2020	J	`jnl`	On Sparsity in Overparametrised Shallow ReLU Networks. CoRR Jaume de Dios, Joan Bruna
2020	J	`jnl`	Overfitting and Optimization in Offline Policy Learning. CoRR David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna
2020	A	`conf`	Provably Efficient Third-Person Imitation from Offline Observation. UAI Aaron Zweig, Joan Bruna
2020	J	`jnl`	Provably Efficient Third-Person Imitation from Offline Observation. CoRR Aaron Zweig, Joan Bruna
2020	A*	`conf`	Pure and Spurious Critical Points: a Geometric Study of Linear Networks. ICLR Matthew Trager, Kathlén Kohn, Joan Bruna
2020	J	`jnl`	Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science. J. Math. Imaging Vis. Joan Bruna, Eldad Haber, Gitta Kutyniok, Thomas Pock, René Vidal
2020	J	`jnl`	Stability Properties of Graph Neural Networks. IEEE Trans. Signal Process. Fernando Gama, Joan Bruna, Alejandro Ribeiro
2020	Misc	`conf`	Stability of Graph Neural Networks to Relative Perturbations. ICASSP Fernando Gama, Alejandro Ribeiro, Joan Bruna
2019	J	`jnl`	Advancing GraphSAGE with A Data-Driven Node Sampling. CoRR Jihun Oh, Kyunghyun Cho, Joan Bruna
2019	A*	`conf`	Approximating Orthogonal Matrices with Effective Givens Factorization. ICML Thomas Frerix, Joan Bruna
2019	A*	`conf`	Deep Geometric Prior for Surface Reconstruction. CVPR Francis Williams, Teseo Schneider, Cláudio T. Silva, Denis Zorin, Joan Bruna, Daniele Panozzo
2019	—	`conf`	Diffusion Scattering Transforms on Graphs. ICLR (Poster) Fernando Gama, Alejandro Ribeiro, Joan Bruna
2019	J	`jnl`	Extra-gradient with player sampling for provable fast convergence in n-player games. CoRR Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna
2019	A*	`conf`	Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias. NeurIPS Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Joan Bruna
2019	J	`jnl`	Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias. CoRR Stéphane d'Ascoli, Levent Sagun, Joan Bruna, Giulio Biroli
2019	J	`jnl`	Global convergence of neuron birth-death dynamics. CoRR Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden
2019	A*	`conf`	Gradient Dynamics of Shallow Univariate ReLU Networks. NeurIPS Francis Williams, Matthew Trager, Daniele Panozzo, Cláudio T. Silva, Denis Zorin, Joan Bruna
2019	J	`jnl`	Gradient Dynamics of Shallow Univariate ReLU Networks. CoRR Francis Williams, Matthew Trager, Cláudio T. Silva, Daniele Panozzo, Denis Zorin, Joan Bruna
2019	A*	`conf`	Neuron birth-death dynamics accelerates gradient descent and converges asymptotically. ICML Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden
2019	J	`jnl`	On the Expected Dynamics of Nonlinear TD Learning. CoRR David Brandfonbrener, Joan Bruna
2019	A*	`conf`	On the Expressive Power of Deep Polynomial Neural Networks. NeurIPS Joe Kileel, Matthew Trager, Joan Bruna
2019	J	`jnl`	On the Expressive Power of Deep Polynomial Neural Networks. CoRR Joe Kileel, Matthew Trager, Joan Bruna
2019	A*	`conf`	On the equivalence between graph isomorphism testing and function approximation with GNNs. NeurIPS Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna
2019	J	`jnl`	On the equivalence between graph isomorphism testing and function approximation with GNNs. CoRR Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna
2019	J	`jnl`	Probing the State of the Art: A Critical Look at Visual Representation Evaluation. CoRR Cinjon Resnick, Zeping Zhan, Joan Bruna
2019	J	`jnl`	Pure and Spurious Critical Points: a Geometric Study of Linear Networks. CoRR Matthew Trager, Kathlén Kohn, Joan Bruna
2019	J	`jnl`	Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes. J. Mach. Learn. Res. Luca Venturi, Afonso S. Bandeira, Joan Bruna
2019	J	`jnl`	Stability Properties of Graph Neural Networks. CoRR Fernando Gama, Joan Bruna, Alejandro Ribeiro
2019	J	`jnl`	Stability of Graph Neural Networks to Relative Perturbations. CoRR Fernando Gama, Joan Bruna, Alejandro Ribeiro
2019	A*	`conf`	Stability of Graph Scattering Transforms. NeurIPS Fernando Gama, Alejandro Ribeiro, Joan Bruna
2019	J	`jnl`	Stability of Graph Scattering Transforms. CoRR Fernando Gama, Joan Bruna, Alejandro Ribeiro
2019	—	`conf`	Supervised Community Detection with Line Graph Neural Networks. ICLR (Poster) Zhengdao Chen, Lisha Li, Joan Bruna
2018	J	`jnl`	Backplay: "Man muss immer umkehren". CoRR Cinjon Resnick, Roberta Raileanu, Sanyam Kapoor, Alex Peysakhovich, Kyunghyun Cho, Joan Bruna
2018	J	`jnl`	Deep Geometric Prior for Surface Reconstruction. CoRR Francis Williams, Teseo Schneider, Cláudio T. Silva, Denis Zorin, Joan Bruna, Daniele Panozzo
2018	J	`jnl`	Diffusion Scattering Transforms on Graphs. CoRR Fernando Gama, Alejandro Ribeiro, Joan Bruna
2018	—	`conf`	Divide and Conquer Networks. ICLR (Poster) Alex Nowak, David Folqué, Joan Bruna
2018	C	`conf`	Graph Neural Networks for IceCube Signal Classification. ICMLA Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna
2018	J	`jnl`	Graph Neural Networks for IceCube Signal Classification. CoRR Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna
2018	J	`jnl`	Kymatio: Scattering Transforms in Python. CoRR Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine Cella, Michael Eickenberg
2018	J	`jnl`	Neural Networks with Finite Intrinsic Dimension have no Spurious Valleys. CoRR Luca Venturi, Afonso S. Bandeira, Joan Bruna
2018	J	`jnl`	Planning with Arithmetic and Geometric Attributes. CoRR David Folqué, Sainbayar Sukhbaatar, Arthur Szlam, Joan Bruna
2018	—	`conf`	Pommerman: A Multi-Agent Playground. AIIDE Workshops Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna
2018	J	`jnl`	Pommerman: A Multi-Agent Playground. CoRR Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna
2018	—	`conf`	Revised Note on Learning Quadratic Assignment with Graph Neural Networks. DSW Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna
2018	A*	`conf`	Surface Networks. CVPR Ilya Kostrikov, Zhongshi Jiang, Daniele Panozzo, Denis Zorin, Joan Bruna
2017	J	`jnl`	A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks. CoRR Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna
2017	J	`jnl`	Few-Shot Learning with Graph Neural Networks. CoRR Victor Garcia Satorras, Joan Bruna
2017	J	`jnl`	Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst
2017	J	`jnl`	Mathematics of Deep Learning. CoRR René Vidal, Joan Bruna, Raja Giryes, Stefano Soatto
2017	J	`jnl`	Surface Networks. CoRR Ilya Kostrikov, Joan Bruna, Daniele Panozzo, Denis Zorin
2017	—	`conf`	Topology and Geometry of Half-Rectified Network Optimization. ICLR (Poster) C. Daniel Freeman, Joan Bruna
2017	—	`conf`	Understanding Trainable Sparse Coding with Matrix Factorization. ICLR (Poster) Thomas Moreau, Joan Bruna
2016	J	`jnl`	A Mathematical Motivation for Complex-Valued Convolutional Networks. Neural Comput. Mark Tygert, Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam
2016	J	`jnl`	Divide and Conquer with Neural Networks. CoRR Alex Nowak, Joan Bruna
2016	J	`jnl`	Geometric deep learning: going beyond Euclidean data. CoRR Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst
2016	J	`jnl`	Inverse Problems with Invariant Multiscale Statistics. CoRR Ivan Dokmanic, Joan Bruna, Stéphane Mallat, Maarten V. de Hoop
2016	A*	`conf`	Super-Resolution with Deep Convolutional Sufficient Statistics. ICLR (Poster) Joan Bruna, Pablo Sprechmann, Yann LeCun
2016	J	`jnl`	Topology and Geometry of Half-Rectified Network Optimization. CoRR C. Daniel Freeman, Joan Bruna
2016	J	`jnl`	Voice Conversion using Convolutional Neural Networks. CoRR Shariq Mobin, Joan Bruna
2015	J	`jnl`	A theoretical argument for complex-valued convolutional networks. CoRR Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert
2015	—	`conf`	Audio Source Separation with Discriminative Scattering Networks. LVA/ICA Pablo Sprechmann, Joan Bruna, Yann LeCun
2015	—	`conf`	Audio Source Separation with Discriminative Scattering Networks. ICLR (Workshop) Pablo Sprechmann, Joan Bruna, Yann LeCun
2015	J	`jnl`	Deep Convolutional Networks on Graph-Structured Data. CoRR Mikael Henaff, Joan Bruna, Yann LeCun
2015	Misc	`conf`	Source separation with scattering Non-Negative Matrix Factorization. ICASSP Joan Bruna, Pablo Sprechmann, Yann LeCun
2015	—	`conf`	Unsupervised Feature Learning from Temporal Data. ICLR (Workshop) Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun
2015	A*	`conf`	Unsupervised Learning of Spatiotemporally Coherent Metrics. ICCV Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun
2014	—	`conf`	Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. NIPS Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus
2014	J	`jnl`	Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation. CoRR Emily Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus
2014	—	`conf`	Intriguing properties of neural networks. ICLR (Poster) Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus
2014	—	`conf`	Spectral Networks and Locally Connected Networks on Graphs. ICLR Joan Bruna, Wojciech Zaremba, Arthur Szlam, Yann LeCun
2014	J	`jnl`	Unsupervised Learning of Spatiotemporally Coherent Metrics. CoRR Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun
2014	J	`jnl`	Video (language) modeling: a baseline for generative models of natural videos. CoRR Marc'Aurelio Ranzato, Arthur Szlam, Joan Bruna, Michaël Mathieu, Ronan Collobert, Sumit Chopra
2013	J	`jnl`	Audio Texture Synthesis with Scattering Moments. CoRR Joan Bruna, Stéphane Mallat
2013	J	`jnl`	Blind Deconvolution with Re-weighted Sparsity Promotion. CoRR Dilip Krishnan, Joan Bruna, Rob Fergus
2013	J	`jnl`	Invariant Scattering Convolution Networks. IEEE Trans. Pattern Anal. Mach. Intell. Joan Bruna, Stéphane Mallat
2013	—	`conf`	Learning Stable Group Invariant Representations with Convolutional Networks ICLR (Workshop Poster) Joan Bruna, Arthur Szlam, Yann LeCun
2013	—	`—`	Scattering Representations for Recognition. (Representations en Scattering pour la Reconaissance). Joan Bruna
2012	J	`jnl`	Invariant Scattering Convolution Networks CoRR Joan Bruna, Stéphane Mallat
2011	J	`jnl`	Classification with Invariant Scattering Representations CoRR Joan Bruna, Stéphane Mallat
2011	—	`conf`	Classification with invariant scattering representations. IVMSP Joan Bruna, Stéphane Mallat
2011	A*	`conf`	Classification with scattering operators. CVPR Joan Bruna, Stéphane Mallat
2011	J	`jnl`	Geometric Models with Co-occurrence Groups CoRR Joan Bruna, Stéphane Mallat
2010	J	`jnl`	Classification with Scattering Operators CoRR Joan Bruna, Stéphane Mallat
2010	B	`conf`	Geometric models with co-occurrence groups. ESANN Joan Bruna, Stéphane Mallat