Stanislas Chambon

According to our database, Stanislas Chambon authored at least 7 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery.

Nicolas Traut, Katja Heuer, Guillaume Lemaître, Anita Beggiato, David Germanaud, Monique Elmaleh, Alban Bethegnies, Laurent Bonnasse-Gahot, Weidong Cai, Stanislas Chambon, Freddy Cliquet, Ayoub Ghriss, Nicolas Guigui, Amicie de Pierrefeu, Meng Wang, Valentina Zantedeschi, Alexandre Boucaud, Joris Van den Bossche, Balázs Kégl, Richard Delorme, Thomas Bourgeron, Roberto Toro, Gaël Varoquaux

NeuroImage, 2022

2021

POT: Python Optimal Transport.

Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

J. Mach. Learn. Res., 2021

2019

Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the Polysomnogram.

Alexander Neergaard Olesen, Stanislas Chambon, Valentin Thorey, Poul Jennum, Emmanuel Mignot, Helge B. D. Sørensen

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018

DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal.

Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal, Emmanuel Mignot, Alexandre Gramfort

CoRR, 2018

Domain adaptation with optimal transport improves EEG sleep stage classifiers.

Stanislas Chambon, Mathieu N. Galtier, Alexandre Gramfort

Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

A Deep Learning Architecture to Detect Events in EEG Signals During Sleep.

Stanislas Chambon, Valentin Thorey, Pierrick J. Arnal, Emmanuel Mignot, Alexandre Gramfort

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

2017

A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series.

Stanislas Chambon, Mathieu Galtier, Pierrick Arnal, Gilles Wainrib, Alexandre Gramfort

CoRR, 2017