| On Lazy Training in Differentiable Programming L Chizat, E Oyallon, F Bach Advances in Neural Information Processing Systems 32, 2937--2947, 2019 | 626 | 2019 |
| i-RevNet: Deep Invertible Networks JH Jacobsen, A Smeulders, E Oyallon International Conference on Learning Representations (ICLR), 2018 | 292 | 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 | 231 | 2015 |
| An Analysis of the SURF Method E Oyallon, J Rabin Image Processing On Line 5, 176-218, 2015 | 151* | 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 | 149 | 2017 |
| 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 | 130 | 2019 |
| Kymatio: Scattering transforms in python M Andreux, T Angles, G Exarchakisgeo, R Leonardu, G Rochette, L Thiry, ... The Journal of Machine Learning Research 21 (1), 2256-2261, 2020 | 111 | 2020 |
| Why do tree-based models still outperform deep learning on tabular data? L Grinsztajn, E Oyallon, G Varoquaux arXiv preprint arXiv:2207.08815, 2022 | 107* | 2022 |
| 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 | 71 | 2018 |
| Decoupled Greedy Learning of CNNs E Belilovsky, M Eickenberg, E Oyallon International Conference on Machine Learning, 736-745, 2020 | 68 | 2020 |
| Generic Deep Networks with Wavelet Scattering E Oyallon, S Mallat, L Sifre International Conference on Learning Representations (ICLR) Workshop track, 2014 | 46* | 2014 |
| Nonlinear Acceleration of CNNs D Scieur, E Oyallon, A d'Aspremont, F Bach International Conference on Learning Representations (ICLR) Workshop track, 2018 | 33* | 2018 |
| 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 | 30 | 2018 |
| 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 | 28* | 2014 |
| Hierarchical Attribute CNNs JH Jacobsen, E Oyallon, S Mallat, AWM Smeulders ICML 2017 Workshop on Principled Approaches to Deep Learning, 2017 | 26* | 2017 |
| Building a Regular Decision Boundary with Deep Networks E Oyallon The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5106-5114, 2017 | 22 | 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 | 14 | 2021 |
| Analyzing and Introducing Structures in Deep Convolutional Neural Networks E Oyallon Paris Sciences et Lettres, 2017 | 9 | 2017 |
| Gradient masked averaging for federated learning I Tenison, SA Sreeramadas, V Mugunthan, E Oyallon, E Belilovsky, I Rish arXiv preprint arXiv:2201.11986, 2022 | 6 | 2022 |
| Interferometric Graph Transform: a Deep Unsupervised Graph Representation E Oyallon International Conference on Machine Learning, 7434-7444, 2020 | 5 | 2020 |
Eugene BelilovskyAssistant Professor, Concordia University and Mila Quebec AI InstituteE-mail megerősítve itt: concordia.ca
