no code implementations • 27 Jul 2022 • Victor Bouvier, Simona Maggio, Alexandre Abraham, Léo Dreyfus-Schmidt
If Uncertainty Quantification (UQ) is crucial to achieve trustworthy Machine Learning (ML), most UQ methods suffer from disparate and inconsistent evaluation protocols.
2 code implementations • 3 Sep 2021 • Alexandre Abraham, Léo Dreyfus-Schmidt
This work explores the effect of noisy sample selection in active learning strategies.
no code implementations • 5 Jul 2021 • Méabh MacMahon, Woochang Hwang, Soorin Yim, Eoghan MacMahon, Alexandre Abraham, Justin Barton, Mukunthan Tharmakulasingam, Paul Bilokon, Vasanthi Priyadarshini Gaddi, Namshik Han
Drug repurposing provides an opportunity to redeploy drugs, which ideally are already approved for use in humans, for the treatment of other diseases.
no code implementations • 18 Dec 2020 • Alexandre Abraham, Léo Dreyfus-Schmidt
Active Learning (AL) is an active domain of research, but is seldom used in the industry despite the pressing needs.
no code implementations • 22 Jan 2018 • Alexandre Gilotte, Clément Calauzènes, Thomas Nedelec, Alexandre Abraham, Simon Dollé
Before A/B testing online a new version of a recommender system, it is usual to perform some offline evaluations on historical data.
no code implementations • 18 Nov 2016 • Alexandre Abraham, Michael Milham, Adriana Di Martino, R. Cameron Craddock, Dimitris Samaras, Bertrand Thirion, Gaël Varoquaux
These R-fMRI pipelines build participant-specific connectomes from functionally-defined brain areas.
no code implementations • 12 Dec 2014 • Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, Gael Varoquaux
Functional Magnetic Resonance Images acquired during resting-state provide information about the functional organization of the brain through measuring correlations between brain areas.
1 code implementation • 12 Dec 2014 • Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Muller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gäel Varoquaux
Statistical machine learning methods are increasingly used for neuroimaging data analysis.