| Why do tree-based models still outperform deep learning on typical tabular data? L Grinsztajn, E Oyallon, G Varoquaux Advances in neural information processing systems 35, 507-520, 2022 | 2567 | 2022 |
| On Lazy Training in Differentiable Programming L Chizat, E Oyallon, F Bach Advances in Neural Information Processing Systems 32, 2937--2947, 2019 | 1285 | 2019 |
| i-RevNet: Deep Invertible Networks JH Jacobsen, A Smeulders, E Oyallon International Conference on Learning Representations (ICLR), 2018 | 448 | 2018 |
| Deep Roto-translation Scattering for Object Classification E Oyallon, S Mallat The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2865-2873, 2015 | 292 | 2015 |
| Greedy Layerwise Learning can Scale to ImageNet E Belilovsky, M Eickenberg, E Oyallon Proceedings of the 36th International Conference on Machine Learning 97, 583-593, 2019 | 267 | 2019 |
| Kymatio: Scattering transforms in python M Andreux, T Angles, G Exarchakis, R Leonarduzzi, G Rochette, L Thiry, ... Journal of Machine Learning Research 21 (60), 1-6, 2020 | 252 | 2020 |
| An Analysis of the SURF Method E Oyallon, J Rabin Image Processing On Line 5, 176-218, 2015 | 232* | 2015 |
| Scaling the Scattering Transform: Deep Hybrid Networks E Oyallon, E Belilovsky, S Zagoruyko The IEEE International Conference on Computer Vision (ICCV), 5618-5627, 2017 | 230 | 2017 |
| Decoupled Greedy Learning of CNNs E Belilovsky, M Eickenberg, E Oyallon International Conference on Machine Learning, 736-745, 2020 | 155 | 2020 |
| Scattering Networks for Hybrid Representation Learning E Oyallon, S Zagoruyko, G Huang, N Komodakis, S Lacoste-Julien, ... IEEE transactions on pattern analysis and machine intelligence 41 (9), 2208-2221, 2018 | 123 | 2018 |
| Generic Deep Networks with Wavelet Scattering E Oyallon, S Mallat, L Sifre International Conference on Learning Representations (ICLR) Workshop track, 2014 | 65* | 2014 |
| Compressing the Input for CNNs with the First-order Scattering Transform E Oyallon, E Belilovsky, S Zagoruyko, M Valko Proceedings of the European Conference on Computer Vision (ECCV), 301-316, 2018 | 44 | 2018 |
| Building a Regular Decision Boundary with Deep Networks E Oyallon The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5106-5114, 2017 | 43 | 2017 |
| Gradient masked averaging for federated learning I Tenison, SA Sreeramadas, V Mugunthan, E Oyallon, I Rish, E Belilovsky Transactions on Machine Learning Research, 2023 | 41 | 2023 |
| Nonlinear Acceleration of CNNs D Scieur, E Oyallon, A d'Aspremont, F Bach International Conference on Learning Representations (ICLR) Workshop track, 2018 | 40* | 2018 |
| Can Forward Gradient Match Backpropagation? L Fournier, S Rivaud, E Belilovsky, M Eickenberg, E Oyallon Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 37 | 2023 |
| Guiding The Last Layer in Federated Learning with Pre-Trained Models G Legate, N Bernier, L Caccia, E Oyallon, E Belilovsky Advances in Neural Information Processing Systems, 2023 | 35 | 2023 |
| Scatnet J Andén, L Sifre, S Mallat, M Kapoko, V Lostanlen, E Oyallon Computer Software. Available: http://www.di.ens.fr/data/software/scatnet, 2014 | 32* | 2014 |
| Hierarchical Attribute CNNs JH Jacobsen, E Oyallon, S Mallat, AWM Smeulders ICML 2017 Workshop on Principled Approaches to Deep Learning, 2017 | 30* | 2017 |
| The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods L Thiry, M Arbel, E Belilovsky, E Oyallon International Conference on Learning Representations, 2021 | 21 | 2021 |
Eugene BelilovskyAssociate Professor, Concordia University and Mila Quebec AI InstituteVerified email at concordia.ca
