| Uncovering the structure of clinical EEG signals with self-supervised learning H Banville, O Chehab, A Hyvärinen, DA Engemann, A Gramfort Journal of Neural Engineering 18 (4), 046020, 2021 | 240 | 2021 |
| A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin–Huxley models M Carlu, O Chehab, L Dalla Porta, D Depannemaecker, C Héricé, ... Journal of neurophysiology 123 (3), 1042-1051, 2020 | 51 | 2020 |
| The optimal noise in noise-contrastive learning is not what you think O Chehab, A Gramfort, A Hyvärinen Uncertainty in Artificial Intelligence (UAI), 307-316, 2022 | 19 | 2022 |
| Deep Recurrent Encoder: an end-to-end network to model magnetoencephalography at scale O Chehab, A Défossez, L Jean-Christophe, A Gramfort, JR King Neurons, Behavior, Data Analysis, and Theory, 2022 | 15* | 2022 |
| Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond O Chehab, A Hyvarinen, A Risteski Spotlight, Advances in Neural Information Processing Systems (NeurIPS) 36, 2024 | 9 | 2024 |
| Learning with self-supervision on EEG data A Gramfort, H Banville, O Chehab, A Hyvärinen, D Engemann International Winter Conference on Brain-Computer Interface (BCI), 1-2, 2021 | 7 | 2021 |
| Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics O Chehab, A Korba, A Stromme, A Vacher International Conference on Learning Representations (ICLR), 2024 | 3 | 2024 |
| Optimizing the noise in self-supervised learning: from importance sampling to noise-contrastive estimation O Chehab, A Gramfort, A Hyvarinen arXiv preprint arXiv:2301.09696, 2023 | 3 | 2023 |
| Polynomial time sampling from log-smooth distributions in fixed dimension under semi-log-concavity of the forward diffusion with application to strongly dissipative distributions A Vacher, O Chehab, A Korba arXiv preprint arXiv:2501.00565, 2024 | 1 | 2024 |
| A Practical Diffusion Path for Sampling O Chehab, A Korba International Conference on Machine Learning (ICML), Workshop on Structured …, 2024 | 1 | 2024 |
| Identifiable Multi-View Causal Discovery Without Non-Gaussianity A Heurtebise, O Chehab, P Ablin, A Gramfort, A Hyvärinen arXiv preprint arXiv:2502.20115, 2025 | | 2025 |
| Density Ratio Estimation with Conditional Probability Paths H Yu, A Klami, A Hyvärinen, A Korba, O Chehab arXiv preprint arXiv:2502.02300, 2025 | | 2025 |
| MVICAD2: Multi-View Independent Component Analysis with Delays and Dilations A Heurtebise, O Chehab, P Ablin, A Gramfort arXiv preprint arXiv:2501.07426, 2025 | | 2025 |
| Advances in Self-Supervised Learning: applications to neuroscience and sample-efficiency O Chehab Inria, Université Paris-Saclay, 2023 | | 2023 |
| The Optimal Noise in Noise-Contrastive Learning Is Not What You Think (Supplementary Material) O Chehab, A Gramfort, A Hyvärinen | | |
Alexandre GramfortMetaPreverjeni e-poštni naslov na meta.com