Edouard Oyallon

ORCID

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 46

Top Venues

PSL Research University, Paris, France (PHD)

Education History

PSL Research University, Paris, France

PHD

Publications

Gwen Legate, Nicolas Bernier, Lucas Caccia, Edouard Oyallon, Eugene Belilovsky
Guiding The Last Layer in Federated Learning with Pre-Trained Models. CoRR (2023)
Gwen Legate, Nicolas Bernier, Lucas Page-Caccia, Edouard Oyallon, Eugene Belilovsky
Guiding The Last Layer in Federated Learning with Pre-Trained Models. NeurIPS (2023)
Léo Grinsztajn, Edouard Oyallon, Myung Jun Kim, Gaël Varoquaux
Vectorizing string entries for data processing on tables: when are larger language models better? CoRR (2023)
Adel Nabli, Edouard Oyallon
DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization. ICML (2023)
Adel Nabli, Eugene Belilovsky, Edouard Oyallon
: Accelerating Asynchronous Communication in Decentralized Deep Learning. CoRR (2023)
Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Can Forward Gradient Match Backpropagation? CoRR (2023)
Adel Nabli, Eugene Belilovsky, Edouard Oyallon
: Accelerating Asynchronous Communication in Decentralized Deep Learning. NeurIPS (2023)
Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Can Forward Gradient Match Backpropagation? ICML (2023)
Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Eugene Belilovsky, Irina Rish
Gradient Masked Averaging for Federated Learning. CoRR (2022)
Adel Nabli, Edouard Oyallon
DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization for Time-Varying Gossips. CoRR (2022)
Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux
Why do tree-based models still outperform deep learning on typical tabular data? NeurIPS (2022)
Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux
Why do tree-based models still outperform deep learning on tabular data? CoRR (2022)
Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon
On Non-Linear operators for Geometric Deep Learning. NeurIPS (2022)
Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon
On Non-Linear operators for Geometric Deep Learning. CoRR (2022)
Othmane Laousy, Guillaume Chassagnon, Edouard Oyallon, Nikos Paragios, Marie-Pierre Revel, Maria Vakalopoulou
Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment. MLMI@MICCAI (2021)
Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods. CoRR (2021)
Nathan Grinsztajn, Philippe Preux, Edouard Oyallon
Low-Rank Projections of GCNs Laplacian. CoRR (2021)
Nathan Grinsztajn, Louis Leconte, Philippe Preux, Edouard Oyallon
Interferometric Graph Transform for Community Labeling. CoRR (2021)
Othmane Laousy, Guillaume Chassagnon, Edouard Oyallon, Nikos Paragios, Marie-Pierre Revel, Maria Vakalopoulou
Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment. CoRR (2021)
Eugene Belilovsky, Louis Leconte, Lucas Caccia, Michael Eickenberg, Edouard Oyallon
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning. CoRR (2021)
Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods. ICLR (2021)
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
Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. 21 (2020)
Edouard Oyallon
Interferometric Graph Transform: a Deep Unsupervised Graph Representation. CoRR (2020)
Edouard Oyallon
Interferometric Graph Transform: a Deep Unsupervised Graph Representation. ICML (2020)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Decoupled Greedy Learning of CNNs. ICML (2020)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Decoupled Greedy Learning of CNNs. CoRR (2019)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Greedy Layerwise Learning Can Scale To ImageNet. ICML (2019)
Lénaïc Chizat, Edouard Oyallon, Francis R. Bach
On Lazy Training in Differentiable Programming. NeurIPS (2019)
Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
Scattering Networks for Hybrid Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. 41 (9) (2019)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko
Compressing the Input for CNNs with the First-Order Scattering Transform. ECCV (9) (2018)
Damien Scieur, Edouard Oyallon, Alexandre d'Aspremont, Francis R. Bach
Nonlinear Acceleration of CNNs. CoRR (2018)
Damien Scieur, Edouard Oyallon, Alexandre d'Aspremont, Francis R. Bach
Nonlinear Acceleration of CNNs. ICLR (Workshop) (2018)
Jörn-Henrik Jacobsen, Arnold W. M. Smeulders, Edouard Oyallon
i-RevNet: Deep Invertible Networks. CoRR (2018)
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
Kymatio: Scattering Transforms in Python. CoRR (2018)
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Greedy Layerwise Learning Can Scale to ImageNet. CoRR (2018)
Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
Scattering Networks for Hybrid Representation Learning. CoRR (2018)
Damien Scieur, Edouard Oyallon, Alexandre d'Aspremont, Francis R. Bach
Nonlinear Acceleration of Deep Neural Networks. CoRR (2018)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko
Compressing the Input for CNNs with the First-Order Scattering Transform. CoRR (2018)
Jörn-Henrik Jacobsen, Arnold W. M. Smeulders, Edouard Oyallon
i-RevNet: Deep Invertible Networks. ICLR (Poster) (2018)
Edouard Oyallon
Building a Regular Decision Boundary with Deep Networks. CoRR (2017)
Jörn-Henrik Jacobsen, Edouard Oyallon, Stéphane Mallat, Arnold W. M. Smeulders
Multiscale Hierarchical Convolutional Networks. CoRR (2017)
Edouard Oyallon
Building a Regular Decision Boundary with Deep Networks. CVPR (2017)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko
Scaling the Scattering Transform: Deep Hybrid Networks. CoRR (2017)
Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko
Scaling the Scattering Transform: Deep Hybrid Networks. ICCV (2017)
Edouard Oyallon, Stéphane Mallat
Deep roto-translation scattering for object classification. CVPR (2015)
Edouard Oyallon, Julien Rabin
An Analysis of the SURF Method. Image Process. Line 5 (2015)
Edouard Oyallon, Stéphane Mallat, Laurent Sifre
Generic Deep Networks with Wavelet Scattering. ICLR (Workshop Poster) (2014)
Edouard Oyallon, Stéphane Mallat
Deep Roto-Translation Scattering for Object Classification. CoRR (2014)

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Publication Activity (10 Years)

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Edouard Oyallon