← Authors

Edouard Oyallon

20 papers · 2015–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (30) 🧭 Keyword Pioneer 🧬 Topic Evolution 🀝 Dynamic Duo (10) πŸš€ Conference Pioneer πŸ’Ž Century Club (20) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (72) πŸ”₯ Unstoppable (7) ❓ The Questioner (2)

Conferences

ICML (6) NIPS (5) ICLR (3) CVPR (2) JMLR (2) ECCV (1) ICCV (1)

Top co-authors

Eugene Belilovsky (10) Michael Eickenberg (5) Adel Nabli (3) Louis Fournier (2) Stephane Rivaud (2) Stephane Mallat (2) Sergey Zagoruyko (2) Louis Thiry (2) Joan Bruna (2) TomΓ‘s Angles (1)

Keywords

convolutional neural network (5) image classification (3) representation learning (2) accelerated gradient (2) decentralized optimization (2) asynchronous optimization (2) neural network (2) greedy learning (2) neural network training (2) distributed optimization (2) graph laplacian (1) geometric deep learning (1) wavelet transform (1) graph representation (1) manifold learning (1) distributed learning (1) feature representation (1) feature extraction (1) gradient estimation (1) neural network optimization (1)

Papers

PETRA: Parallel End-to-end Training with Reversible Architectures ICLR 2025
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction ICML 2025
Decentralized Asynchronous Optimization with DADAO allows Decoupling and Acceleration JMLR 2025
Can Forward Gradient Match Backpropagation? ICML 2023
$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning NIPS 2023
Guiding The Last Layer in Federated Learning with Pre-Trained Models NIPS 2023
DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization ICML 2023
Why do tree-based models still outperform deep learning on typical tabular data? NIPS 2022
On Non-Linear operators for Geometric Deep Learning NIPS 2022
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods ICLR 2021
Decoupled Greedy Learning of CNNs ICML 2020
Kymatio: Scattering Transforms in Python JMLR 2020
Interferometric Graph Transform: a Deep Unsupervised Graph Representation ICML 2020
On Lazy Training in Differentiable Programming NIPS 2019
Greedy Layerwise Learning Can Scale To ImageNet ICML 2019
i-RevNet: Deep Invertible Networks ICLR 2018
Compressing the Input for CNNs with the First-Order Scattering Transform ECCV 2018
Scaling the Scattering Transform: Deep Hybrid Networks ICCV 2017
Building a Regular Decision Boundary With Deep Networks CVPR 2017
Deep Roto-Translation Scattering for Object Classification CVPR 2015