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  • Edouard Oyallon

  • Chargé de Recherche
  • Équipe: MLIA


  • Louis Fournier, Adeetya Patel, Michael Eickenberg, Edouard Oyallon, Eugene Belilovsky. Preventing Dimensional Collapse in Contrastive Local Learning with Subsampling. ICML 2023 Workshop on Localized Learning (LLW), Jul 2023, Honolulu (Hawaii), USA, United States. ⟨hal-04156218⟩
  • Adel Nabli, Eugene Belilovsky, Edouard Oyallon. $\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning. 2023. ⟨hal-04124318⟩
  • Louis Fournier, Stéphane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon. Can Forward Gradient Match Backpropagation?. Fortieth International Conference on Machine Learning, Jul 2023, Honolulu (Hawaii), USA, United States. ⟨hal-04119829⟩
  • Adel Nabli, Edouard Oyallon. DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization. 2023. ⟨hal-03737694v2⟩
  • Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon. On Non-Linear operators for Geometric Deep Learning. 2023. ⟨hal-03711864v2⟩
  • Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux. Why do tree-based models still outperform deep learning on typical tabular data?. 36th Conference on Neural Information Processing Systems (NeurIPS 2022) Track on Datasets and Benchmarks, Nov 2022, New Orleans, United States. ⟨hal-03723551v3⟩