Fast approximate natural gradient descent in a kronecker factored eigenbasis T George, C Laurent, X Bouthillier, N Ballas, P Vincent Advances in Neural Information Processing Systems 31, 2018 | 124 | 2018 |
Implicit regularization via neural feature alignment A Baratin, T George, C Laurent, R Devon Hjelm, G Lajoie, P Vincent, ... The 24th International Conference on Artificial Intelligence and Statistics …, 2020 | 53* | 2020 |
Continual learning in deep networks: an analysis of the last layer T Lesort, T George, I Rish arXiv preprint arXiv:2106.01834, 2021 | 18 | 2021 |
Revisiting loss modelling for unstructured pruning C Laurent, C Ballas, T George, N Ballas, P Vincent arXiv preprint arXiv:2006.12279, 2020 | 9 | 2020 |
NNGeometry: easy and fast fisher information matrices and neural tangent kernels in PyTorch T George | 7 | 2020 |
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty T George, G Lajoie, A Baratin Transactions on Machine Learning Research, 2022 | 3 | 2022 |
An evaluation of fisher approximations beyond kronecker factorization C Laurent, T George, X Bouthillier, N Ballas, P Vincent | 3 | 2018 |
The Dynamics of Functional Diversity throughout Neural Network Training L Zamparo, ME Brunet, T George, S Kharaghani, GK Dziugaite NeurIPS 2021 Workshop BDL, 2021 | 1 | 2021 |
A Transfer Learning Pipeline for Educational Resource Discovery with Application in Survey Generation I Li, T George, A Fabbri, T Liao, B Chen, R Kawamura, R Zhou, V Yan, ... Proceedings of the 18th Workshop on Innovative Use of NLP for Building …, 2023 | | 2023 |
Deep networks training and generalization: insights from linearization T George | | 2023 |
Factorized second order methods in neural networks T George | | 2017 |