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Alexandre Gramfort
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Publications
- 2023
- [c80]Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort:
Multiview Independent Component Analysis with Delays. MLSP 2023: 1-6 - [i72]Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort:
MultiView Independent Component Analysis with Delays. CoRR abs/2312.00484 (2023) - 2022
- [c74]Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter:
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. NeurIPS 2022 - [i66]Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter:
Benchopt: Reproducible, efficient and collaborative optimization benchmarks. CoRR abs/2206.13424 (2022) - 2021
- [j32]Ronan Perry, Gavin Mischler, Richard Guo, Theo Lee, Alexander Chang, Arman Koul, Cameron Franz, Hugo Richard, Iain Carmichael, Pierre Ablin, Alexandre Gramfort, Joshua T. Vogelstein:
mvlearn: Multiview Machine Learning in Python. J. Mach. Learn. Res. 22: 109:1-109:7 (2021) - [c64]Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen:
Shared Independent Component Analysis for Multi-Subject Neuroimaging. NeurIPS 2021: 29962-29971 - [i61]Hugo Richard, Pierre Ablin, Aapo Hyvärinen, Alexandre Gramfort, Bertrand Thirion:
Adaptive Multi-View ICA: Estimation of noise levels for optimal inference. CoRR abs/2102.10964 (2021) - [i53]Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen:
Shared Independent Component Analysis for Multi-Subject Neuroimaging. CoRR abs/2110.13502 (2021) - 2020
- [j29]David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann:
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. NeuroImage 222: 116893 (2020) - [c58]Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin:
Modeling Shared responses in Neuroimaging Studies through MultiView ICA. NeurIPS 2020 - [i45]Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin:
Modeling Shared Responses in Neuroimaging Studies through MultiView ICA. CoRR abs/2006.06635 (2020) - 2019
- [c56]Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso, Francis R. Bach:
Stochastic algorithms with descent guarantees for ICA. AISTATS 2019: 1564-1573 - [c55]Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort:
Beyond Pham's algorithm for joint diagonalization. ESANN 2019 - [c54]Pierre Ablin, Dylan Fagot, Herwig Wendt, Alexandre Gramfort, Cédric Févotte:
A Quasi-Newton Algorithm on the Orthogonal Manifold for NMF with Transform Learning. ICASSP 2019: 700-704 - [c50]David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann:
Manifold-regression to predict from MEG/EEG brain signals without source modeling. NeurIPS 2019: 7321-7332 - [c49]Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort:
Learning step sizes for unfolded sparse coding. NeurIPS 2019: 13100-13110 - [i36]Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort:
Learning step sizes for unfolded sparse coding. CoRR abs/1905.11071 (2019) - [i35]David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann:
Manifold-regression to predict from MEG/EEG brain signals without source modeling. CoRR abs/1906.02687 (2019) - 2018
- [j26]Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort:
Faster Independent Component Analysis by Preconditioning With Hessian Approximations. IEEE Trans. Signal Process. 66(15): 4040-4049 (2018) - [c47]Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort:
Accelerating Likelihood Optimization for ICA on Real Signals. LVA/ICA 2018: 151-160 - [c45]Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort:
Faster ICA Under Orthogonal Constraint. ICASSP 2018: 4464-4468 - [i28]Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso, Francis R. Bach:
EM algorithms for ICA. CoRR abs/1805.10054 (2018) - [i27]Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort:
Accelerating likelihood optimization for ICA on real signals. CoRR abs/1806.09390 (2018) - [i25]Pierre Ablin, Dylan Fagot, Herwig Wendt, Alexandre Gramfort, Cédric Févotte:
A Quasi-Newton algorithm on the orthogonal manifold for NMF with transform learning. CoRR abs/1811.02225 (2018) - [i24]Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort:
Beyond Pham's algorithm for joint diagonalization. CoRR abs/1811.11433 (2018)
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