63.6k citations · 65.9k across the 85 of their papers we have counts for
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MultiView Independent Component Analysis with Delays
Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
Linear Independent Component Analysis (ICA) is a blind source separation technique that has been used in various domains to identify independent latent sources from observed signal…
Data augmentation for learning predictive models on EEG: a systematic comparison
Cédric Rommel, Joseph Paillard, Thomas Moreau +1
Objective: The use of deep learning for electroencephalography (EEG) classification tasks has been rapidly growing in the last years, yet its application has been limited by the re…
Benchopt: Reproducible, efficient and collaborative optimization benchmarks
Thomas Moreau, Mathurin Massias, Alexandre Gramfort +18
Numerical validation is at the core of machine learning research as it allows to assess the actual impact of new methods, and to confirm the agreement between theory and practice.…
Deep invariant networks with differentiable augmentation layers
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
Designing learning systems which are invariant to certain data transformations is critical in machine learning. Practitioners can typically enforce a desired invariance on the trai…
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
Kenan Šehić, Alexandre Gramfort, Joseph Salmon +1
While Weighted Lasso sparse regression has appealing statistical guarantees that would entail a major real-world impact in finance, genomics, and brain imaging applications, it is…
Shared Independent Component Analysis for Multi-Subject Neuroimaging
Hugo Richard, Pierre Ablin, Bertrand Thirion +2
We consider shared response modeling, a multi-view learning problem where one wants to identify common components from multiple datasets or views. We introduce Shared Independent C…