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Pierre Ablin

Ecole normale supérieure, Paris, France

Benchopt: Reproducible, efficient and collaborative optimization benchmarks


Jun 28, 2022
Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoit Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter


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Do Residual Neural Networks discretize Neural Ordinary Differential Equations?


May 29, 2022
Michael E. Sander, Pierre Ablin, Gabriel Peyré

* 27 pages 

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A framework for bilevel optimization that enables stochastic and global variance reduction algorithms


Jan 31, 2022
Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau


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Shared Independent Component Analysis for Multi-Subject Neuroimaging


Oct 26, 2021
Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo HyvÀrinen

* Accepted at NeurIPS 2021 

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Sinkformers: Transformers with Doubly Stochastic Attention


Oct 22, 2021
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré

* 26 pages 

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Kernel Stein Discrepancy Descent


May 20, 2021
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin


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Adaptive Multi-View ICA: Estimation of noise levels for optimal inference


Feb 22, 2021
Hugo Richard, Pierre Ablin, Aapo HyvÀrinen, Alexandre Gramfort, Bertrand Thirion


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Momentum Residual Neural Networks


Feb 15, 2021
Michael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré

* 34 pages 

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Fast and accurate optimization on the orthogonal manifold without retraction


Feb 15, 2021
Pierre Ablin, Gabriel Peyré

* 23 pages 

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Deep orthogonal linear networks are shallow


Nov 27, 2020
Pierre Ablin


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