| Learning with random learning rates L Blier, P Wolinski, Y Ollivier arXiv preprint arXiv:1810.01322, 2018 | 22 | 2018 |
| Gaussian Pre-Activations in Neural Networks: Myth or Reality? P Wolinski, J Arbel arXiv preprint arXiv:2205.12379, 2022 | 4 | 2022 |
| Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review MT Lê, P Wolinski, J Arbel arXiv preprint arXiv:2311.11883, 2023 | 3 | 2023 |
| Rethinking Gauss-Newton for learning over-parameterized models M Arbel, R Ménégaux, P Wolinski Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 2 | 2023 |
| An Equivalence between Bayesian Priors and Penalties in Variational Inference P Wolinski, G Charpiat, Y Ollivier arXiv preprint arXiv:2002.00178, 2020 | 2* | 2020 |
| Asymmetrical scaling layers for stable network pruning P Wolinski, G Charpiat, Y Ollivier OpenReview Archive, 2020 | 1 | 2020 |
| Structural Learning of Neural Networks P Wolinski TAU Team, LRI, Inria, University Paris-Saclay, 2020 | 1 | 2020 |
| Adapting Newton's Method to Neural Networks through a Summary of Higher-Order Derivatives P Wolinski arXiv preprint arXiv:2312.03885, 2023 | | 2023 |
| Structural Learning of Neural Networks PhD Defense P Wolinski | | 2020 |
Julyan ArbelInriaVerified email at inria.fr
