Pierre Ablin
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Citée par
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
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
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
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
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
Faster ICA under orthogonal constraint
P Ablin, JF Cardoso, A Gramfort
ICASSP, 2018
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
Beyond Pham's algorithm for joint diagonalization
P Ablin, JF Cardoso, A Gramfort
27th European Symposium on Artificial Neural Networks, Computational …, 2019
Momentum residual neural networks
ME Sander, P Ablin, M Blondel, G Peyré
arXiv preprint arXiv:2102.07870, 2021
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
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
mvlearn: Multiview Machine Learning in Python
R Perry, G Mischler, R Guo, T Lee, A Chang, A Koul, C Franz, H Richard, ...
Journal of Machine Learning Research 22 (109), 1-7, 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
Accelerating likelihood optimization for ICA on real signals
P Ablin, JF Cardoso, A Gramfort
International Conference on Latent Variable Analysis and Signal Separation …, 2018
Detecting myocardial infarction using medial surfaces
P Ablin, K Siddiqi
Statistical Atlases and Computational Models of the Heart, 146-153, 2015
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
Kernel Stein Discrepancy Descent
A Korba, PC Aubin-Frankowski, S Majewski, P Ablin
arXiv preprint arXiv:2105.09994, 2021
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference
H Richard, P Ablin, A Hyvärinen, A Gramfort, B Thirion
arXiv preprint arXiv:2102.10964, 2021
Fast and accurate optimization on the orthogonal manifold without retraction
P Ablin, G Peyré
arXiv preprint arXiv:2102.07432, 2021
Deep orthogonal linear networks are shallow
P Ablin
arXiv preprint arXiv:2011.13831, 2020
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