| Faster independent component analysis by preconditioning with Hessian approximations P Ablin, JF Cardoso, A Gramfort IEEE Transactions on Signal Processing 66 (15), 4040-4049, 2018 | 67 | 2018 |
| Statistical shape modeling of the left ventricle: myocardial infarct classification challenge A Suinesiaputra, P Ablin, X Alba, M Alessandrini, J Allen, W Bai, S Cimen, ... IEEE journal of biomedical and health informatics 22 (2), 503-515, 2017 | 54 | 2017 |
| Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states D Sabbagh, P Ablin, G Varoquaux, A Gramfort, DA Engemann NeuroImage 222, 116893, 2020 | 41 | 2020 |
| Learning step sizes for unfolded sparse coding P Ablin, T Moreau, M Massias, A Gramfort Advances in Neural Information Processing Systems 32, 13100--13110, 2019 | 39 | 2019 |
| Super-efficiency of automatic differentiation for functions defined as a minimum P Ablin, G Peyré, T Moreau International Conference on Machine Learning, 32-41, 2020 | 38 | 2020 |
| Manifold-regression to predict from MEG/EEG brain signals without source modeling D Sabbagh, P Ablin, G Varoquaux, A Gramfort, DA Engemann Advances in Neural Information Processing Systems 32 32, 7323-7334, 2019 | 34 | 2019 |
| Momentum residual neural networks ME Sander, P Ablin, M Blondel, G Peyré Proceedings of the 38th International Conference on Machine Learning 139, 2021 | 27 | 2021 |
| Faster ICA under orthogonal constraint P Ablin, JF Cardoso, A Gramfort ICASSP, 2018 | 24 | 2018 |
| Beyond Pham's algorithm for joint diagonalization P Ablin, JF Cardoso, A Gramfort 27th European Symposium on Artificial Neural Networks, Computational …, 2019 | 17 | 2019 |
| Modeling shared responses in neuroimaging studies through Multiview ICA H Richard, L Gresele, A Hyvärinen, B Thirion, A Gramfort, P Ablin Advances in Neural Information Processing Systems 33, 19149--19162, 2020 | 12 | 2020 |
| Stochastic algorithms with descent guarantees for ICA P Ablin, A Gramfort, JF Cardoso, F Bach The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 9* | 2019 |
| Spectral independent component analysis with noise modeling for M/EEG source separation P Ablin, JF Cardoso, A Gramfort Journal of Neuroscience Methods 356, 109144, 2021 | 8 | 2021 |
| A quasi-Newton algorithm on the orthogonal manifold for NMF with transform learning P Ablin, D Fagot, H Wendt, A Gramfort, C Févotte ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 8 | 2019 |
| mvlearn: Multiview Machine Learning in Python. R Perry, G Mischler, R Guo, T Lee, A Chang, A Koul, C Franz, H Richard, ... J. Mach. Learn. Res. 22, 109:1-109:7, 2021 | 7 | 2021 |
| Sinkformers: Transformers with doubly stochastic attention ME Sander, P Ablin, M Blondel, G Peyré International Conference on Artificial Intelligence and Statistics, 3515-3530, 2022 | 5 | 2022 |
| Fast and accurate optimization on the orthogonal manifold without retraction P Ablin, G Peyré International Conference on Artificial Intelligence and Statistics, 5636-5657, 2022 | 5 | 2022 |
| Kernel Stein Discrepancy Descent A Korba, PC Aubin-Frankowski, S Majewski, P Ablin Proceedings of the 38th International Conference on Machine Learning 139, 2021 | 5 | 2021 |
| Accelerating likelihood optimization for ICA on real signals P Ablin, JF Cardoso, A Gramfort International Conference on Latent Variable Analysis and Signal Separation …, 2018 | 3 | 2018 |
| A framework for bilevel optimization that enables stochastic and global variance reduction algorithms M Dagréou, P Ablin, S Vaiter, T Moreau Advances in Neural Information Processing Systems 35, 2022 | 2 | 2022 |
| Detecting myocardial infarction using medial surfaces P Ablin, K Siddiqi Statistical Atlases and Computational Models of the Heart, 146-153, 2015 | 2 | 2015 |
Alexandre GramfortINRIA, Univ. Paris-SaclayVerified email at inria.fr
