Joan Bruna

According to our database, Joan Bruna authored at least 121 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Neural Galerkin schemes with active learning for high-dimensional evolution equations.

Joan Bruna, Benjamin Peherstorfer, Eric Vanden-Eijnden

J. Comput. Phys., January, 2024

Computational-Statistical Gaps in Gaussian Single-Index Models.

Alex Damian, Loucas Pillaud-Vivien, Jason D. Lee, Joan Bruna

CoRR, 2024

2023

Stochastic Optimal Control Matching.

Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen

CoRR, 2023

On Learning Gaussian Multi-index Models with Gradient Flow.

Alberto Bietti, Joan Bruna, Loucas Pillaud-Vivien

CoRR, 2023

Symmetric Single Index Learning.

Aaron Zweig, Joan Bruna

CoRR, 2023

Data-driven multiscale modeling of subgrid parameterizations in climate models.

Karl Otness, Laure Zanna, Joan Bruna

CoRR, 2023

On Single-Index Models beyond Gaussian Data.

Aaron Zweig, Loucas Pillaud-Vivien, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks.

Vignesh Kothapalli, Tom Tirer, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation.

David Brandfonbrener, Ofir Nachum, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Conditionally Strongly Log-Concave Generative Models.

Florentin Guth, Etienne Lempereur, Joan Bruna, Stéphane Mallat

Proceedings of the International Conference on Machine Learning, 2023

Beyond the Edge of Stability via Two-step Gradient Updates.

Lei Chen, Joan Bruna

Proceedings of the International Conference on Machine Learning, 2023

2022

Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks.

Pau Batlle, Joan Bruna, Carlos Fernandez-Granda, Victor M. Preciado

SIAM J. Control. Optim., 2022

Guest Editorial: Non-Euclidean Machine Learning.

Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Depth separation beyond radial functions.

Luca Venturi, Samy Jelassi, Tristan Ozuch, Joan Bruna

J. Mach. Learn. Res., 2022

A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks.

Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna

CoRR, 2022

Towards Antisymmetric Neural Ansatz Separation.

Aaron Zweig, Joan Bruna

CoRR, 2022

On Gradient Descent Convergence beyond the Edge of Stability.

Lei Chen, Joan Bruna

CoRR, 2022

Neural Galerkin Scheme with Active Learning for High-Dimensional Evolution Equations.

Joan Bruna, Benjamin Peherstorfer, Eric Vanden-Eijnden

CoRR, 2022

Exponential Separations in Symmetric Neural Networks.

Aaron Zweig, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Non-Linear operators for Geometric Deep Learning.

Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When does return-conditioned supervised learning work for offline reinforcement learning?

David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning single-index models with shallow neural networks.

Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Extended Unconstrained Features Model for Exploring Deep Neural Collapse.

Tom Tirer, Joan Bruna

Proceedings of the International Conference on Machine Learning, 2022

On feature learning in neural networks with global convergence guarantees.

Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna

Proceedings of the Tenth International Conference on Learning Representations, 2022

Cartoon Explanations of Image Classifiers.

Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok

Proceedings of the Computer Vision - ECCV 2022, 2022

Neural Fields as Learnable Kernels for 3D Reconstruction.

Francis Williams, Zan Gojcic, Sameh Khamis, Denis Zorin, Joan Bruna, Sanja Fidler, Or Litany

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Lattice-Based Methods Surpass Sum-of-Squares in Clustering.

Ilias Zadik, Min Jae Song, Alexander S. Wein, Joan Bruna

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Quantile Filtered Imitation Learning.

David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna

CoRR, 2021

Multi-fidelity Stability for Graph Representation Learning.

Yihan He, Joan Bruna

CoRR, 2021

Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks.

Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden

CoRR, 2021

On the Sample Complexity of Learning with Geometric Stability.

Alberto Bietti, Luca Venturi, Joan Bruna

CoRR, 2021

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

Michael M. Bronstein, Joan Bruna, Taco Cohen, Petar Velickovic

CoRR, 2021

Symmetry Breaking in Symmetric Tensor Decomposition.

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

CoRR, 2021

Self-Supervised Equivariant Scene Synthesis from Video.

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

CoRR, 2021

On the Cryptographic Hardness of Learning Single Periodic Neurons.

Min Jae Song, Ilias Zadik, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Extensible Benchmark Suite for Learning to Simulate Physical Systems.

Karl Otness, Arvi Gjoka, Joan Bruna, Daniele Panozzo, Benjamin Peherstorfer, Teseo Schneider, Denis Zorin

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Offline RL Without Off-Policy Evaluation.

David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Sample Complexity of Learning under Geometric Stability.

Alberto Bietti, Luca Venturi, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Kernel-Based Smoothness Analysis of Residual Networks.

Tom Tirer, Joan Bruna, Raja Giryes

Proceedings of the Mathematical and Scientific Machine Learning, 2021

A Functional Perspective on Learning Symmetric Functions with Neural Networks.

Aaron Zweig, Joan Bruna

Proceedings of the 38th International Conference on Machine Learning, 2021

On Energy-Based Models with Overparametrized Shallow Neural Networks.

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

Proceedings of the 38th International Conference on Machine Learning, 2021

Offline Contextual Bandits with Overparameterized Models.

David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna

Proceedings of the 38th International Conference on Machine Learning, 2021

On Graph Neural Networks versus Graph-Augmented MLPs.

Lei Chen, Zhengdao Chen, Joan Bruna

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning the Relevant Substructures for Tasks on Graph Data.

Lei Chen, Zhengdao Chen, Joan Bruna

Proceedings of the IEEE International Conference on Acoustics, 2021

Neural Splines: Fitting 3D Surfaces With Infinitely-Wide Neural Networks.

Francis Williams, Matthew Trager, Joan Bruna, Denis Zorin

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

A Permutation-Equivariant Neural Network Architecture For Auction Design.

Jad Rahme, Samy Jelassi, Joan Bruna, S. Matthew Weinberg

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Stability Properties of Graph Neural Networks.

Fernando Gama, Joan Bruna, Alejandro Ribeiro

IEEE Trans. Signal Process., 2020

Kymatio: Scattering Transforms in Python.

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-Emanuele Cella, Michael Eickenberg

J. Mach. Learn. Res., 2020

Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science.

Joan Bruna, Eldad Haber, Gitta Kutyniok, Thomas Pock, René Vidal

J. Math. Imaging Vis., 2020

Continuous LWE.

Joan Bruna, Oded Regev, Min Jae Song, Yi Tang

Electron. Colloquium Comput. Complex., 2020

Learned Equivariant Rendering without Transformation Supervision.

Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho

CoRR, 2020

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

Donsub Rim, Luca Venturi, Joan Bruna, Benjamin Peherstorfer

CoRR, 2020

In-Distribution Interpretability for Challenging Modalities.

Cosmas Heiß, Ron Levie, Cinjon Resnick, Gitta Kutyniok, Joan Bruna

CoRR, 2020

Overfitting and Optimization in Offline Policy Learning.

David Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna

CoRR, 2020

On Sparsity in Overparametrised Shallow ReLU Networks.

Jaume de Dios, Joan Bruna

CoRR, 2020

Provably Efficient Third-Person Imitation from Offline Observation.

Aaron Zweig, Joan Bruna

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

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

Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Dynamical Central Limit Theorem for Shallow Neural Networks.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Can Graph Neural Networks Count Substructures?

Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Rate-Distortion Framework for Explaining Black-Box Model Decisions.

Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok

Proceedings of the xxAI - Beyond Explainable AI, 2020

Extra-gradient with player sampling for faster convergence in n-player games.

Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna

Proceedings of the 37th International Conference on Machine Learning, 2020

Pure and Spurious Critical Points: a Geometric Study of Linear Networks.

Matthew Trager, Kathlén Kohn, Joan Bruna

Proceedings of the 8th International Conference on Learning Representations, 2020

Geometric Insights into the Convergence of Nonlinear TD Learning.

David Brandfonbrener, Joan Bruna

Proceedings of the 8th International Conference on Learning Representations, 2020

Stability of Graph Neural Networks to Relative Perturbations.

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes.

Luca Venturi, Afonso S. Bandeira, Joan Bruna

J. Mach. Learn. Res., 2019

Probing the State of the Art: A Critical Look at Visual Representation Evaluation.

Cinjon Resnick, Zeping Zhan, Joan Bruna

CoRR, 2019

Extra-gradient with player sampling for provable fast convergence in n-player games.

Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna

CoRR, 2019

On the Expected Dynamics of Nonlinear TD Learning.

David Brandfonbrener, Joan Bruna

CoRR, 2019

Advancing GraphSAGE with A Data-Driven Node Sampling.

Jihun Oh, Kyunghyun Cho, Joan Bruna

CoRR, 2019

Global convergence of neuron birth-death dynamics.

Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden

CoRR, 2019

Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias.

Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Gradient Dynamics of Shallow Univariate ReLU Networks.

Francis Williams, Matthew Trager, Daniele Panozzo, Cláudio T. Silva, Denis Zorin, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Expressive Power of Deep Polynomial Neural Networks.

Joe Kileel, Matthew Trager, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stability of Graph Scattering Transforms.

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the equivalence between graph isomorphism testing and function approximation with GNNs.

Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Neuron birth-death dynamics accelerates gradient descent and converges asymptotically.

Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden

Proceedings of the 36th International Conference on Machine Learning, 2019

Approximating Orthogonal Matrices with Effective Givens Factorization.

Thomas Frerix, Joan Bruna

Proceedings of the 36th International Conference on Machine Learning, 2019

Diffusion Scattering Transforms on Graphs.

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Proceedings of the 7th International Conference on Learning Representations, 2019

Supervised Community Detection with Line Graph Neural Networks.

Zhengdao Chen, Lisha Li, Joan Bruna

Proceedings of the 7th International Conference on Learning Representations, 2019

Deep Geometric Prior for Surface Reconstruction.

Francis Williams, Teseo Schneider, Cláudio T. Silva, Denis Zorin, Joan Bruna, Daniele Panozzo

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Kymatio: Scattering Transforms in Python.

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-Emanuele Cella, Michael Eickenberg

CoRR, 2018

Planning with Arithmetic and Geometric Attributes.

David Folqué, Sainbayar Sukhbaatar, Arthur Szlam, Joan Bruna

CoRR, 2018

Backplay: "Man muss immer umkehren".

Cinjon Resnick, Roberta Raileanu, Sanyam Kapoor, Alex Peysakhovich, Kyunghyun Cho, Joan Bruna

CoRR, 2018

Neural Networks with Finite Intrinsic Dimension have no Spurious Valleys.

Luca Venturi, Afonso S. Bandeira, Joan Bruna

CoRR, 2018

Graph Neural Networks for IceCube Signal Classification.

Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Few-Shot Learning with Graph Neural Networks.

Victor Garcia Satorras, Joan Bruna Estrach

Proceedings of the 6th International Conference on Learning Representations, 2018

Divide and Conquer Networks.

Alex Nowak, David Folqué, Joan Bruna

Proceedings of the 6th International Conference on Learning Representations, 2018

Revised Note on Learning Quadratic Assignment with Graph Neural Networks.

Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna

Proceedings of the 2018 IEEE Data Science Workshop, 2018

Surface Networks.

Ilya Kostrikov, Zhongshi Jiang, Daniele Panozzo, Denis Zorin, Joan Bruna

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Pommerman: A Multi-Agent Playground.

Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna

Proceedings of the Joint Proceedings of the AIIDE 2018 Workshops co-located with 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2018), 2018

2017

Geometric Deep Learning: Going beyond Euclidean data.

Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst

IEEE Signal Process. Mag., 2017

Mathematics of Deep Learning.

René Vidal, Joan Bruna, Raja Giryes, Stefano Soatto

CoRR, 2017

A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks.

Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna

CoRR, 2017

Surface Networks.

Ilya Kostrikov, Joan Bruna, Daniele Panozzo, Denis Zorin

CoRR, 2017

Understanding Trainable Sparse Coding with Matrix Factorization.

Thomas Moreau, Joan Bruna

Proceedings of the 5th International Conference on Learning Representations, 2017

Topology and Geometry of Half-Rectified Network Optimization.

C. Daniel Freeman, Joan Bruna

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

A Mathematical Motivation for Complex-Valued Convolutional Networks.

Mark Tygert, Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam

Neural Comput., 2016

Divide and Conquer with Neural Networks.

Alex Nowak, Joan Bruna

CoRR, 2016

Voice Conversion using Convolutional Neural Networks.

Shariq Mobin, Joan Bruna

CoRR, 2016

Inverse Problems with Invariant Multiscale Statistics.

Ivan Dokmanic, Joan Bruna, Stéphane Mallat, Maarten V. de Hoop

CoRR, 2016

Super-Resolution with Deep Convolutional Sufficient Statistics.

Joan Bruna, Pablo Sprechmann, Yann LeCun

Proceedings of the 4th International Conference on Learning Representations, 2016

2015

Audio Source Separation with Discriminative Scattering Networks.

Pablo Sprechmann, Joan Bruna, Yann LeCun

Proceedings of the 3rd International Conference on Learning Representations, 2015

Deep Convolutional Networks on Graph-Structured Data.

Mikael Henaff, Joan Bruna, Yann LeCun

CoRR, 2015

Unsupervised Feature Learning from Temporal Data.

Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

Proceedings of the 3rd International Conference on Learning Representations, 2015

A theoretical argument for complex-valued convolutional networks.

Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert

CoRR, 2015

Unsupervised Learning of Spatiotemporally Coherent Metrics.

Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Source separation with scattering Non-Negative Matrix Factorization.

Joan Bruna, Pablo Sprechmann, Yann LeCun

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014

Intriguing properties of neural networks.

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J. Goodfellow, Rob Fergus

Proceedings of the 2nd International Conference on Learning Representations, 2014

Video (language) modeling: a baseline for generative models of natural videos.

Marc'Aurelio Ranzato, Arthur Szlam, Joan Bruna, Michaël Mathieu, Ronan Collobert, Sumit Chopra

CoRR, 2014

Spectral Networks and Locally Connected Networks on Graphs.

Joan Bruna, Wojciech Zaremba, Arthur Szlam, Yann LeCun

Proceedings of the 2nd International Conference on Learning Representations, 2014

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation.

Emily L. Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Signal recovery from Pooling Representations.

Joan Bruna Estrach, Arthur Szlam, Yann LeCun

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Scattering Representations for Recognition. (Representations en Scattering pour la Reconaissance).

Joan Bruna

PhD thesis, 2013

Invariant Scattering Convolution Networks.

Joan Bruna, Stéphane Mallat

IEEE Trans. Pattern Anal. Mach. Intell., 2013

Learning Stable Group Invariant Representations with Convolutional Networks

Joan Bruna, Arthur Szlam, Yann LeCun

Proceedings of the 1st International Conference on Learning Representations, 2013

Blind Deconvolution with Re-weighted Sparsity Promotion.

Dilip Krishnan, Joan Bruna, Rob Fergus

CoRR, 2013

Audio Texture Synthesis with Scattering Moments.

Joan Bruna, Stéphane Mallat

CoRR, 2013

2011

Classification with invariant scattering representations.

Joan Bruna, Stéphane Mallat

Proceedings of the IEEE 10th Image, 2011

Classification with scattering operators.

Joan Bruna, Stéphane Mallat

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Geometric models with co-occurrence groups.

Joan Bruna, Stéphane Mallat

Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010