Adaptive Subsampling of Multidomain Signals with Product Graphs. - Théo Gnassounou; Pierre Humbert; Laurent Oudre (ICASSP, 2021)

Convolution Monge Mapping Normalization for learning on sleep data. - Théo Gnassounou; Rémi Flamary; Alexandre Gramfort (NeurIPS, 2023)

Convolutional Monge Mapping Normalization for learning on biosignals. - Théo Gnassounou; Rémi Flamary; Alexandre Gramfort (CoRR, 2023)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation. - Yanis Lalou; Théo Gnassounou; Antoine Collas; Antoine de Mathelin; Oleksii Kachaiev; Ambroise Odonnat; Alexandre Gramfort; Thomas Moreau 001; Rémi Flamary (CoRR, 2024)

Multi-Source and Test-Time Domain Adaptation on Multivariate Signals using Spatio-Temporal Monge Alignment. - Théo Gnassounou; Antoine Collas; Rémi Flamary; Karim Lounici; Alexandre Gramfort (CoRR, 2024)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities. - Yanis Lalou; Théo Gnassounou; Antoine Collas; Antoine de Mathelin; Ambroise Odonnat; Thomas Moreau 001; Alexandre Gramfort; Rémi Flamary (Trans. Mach. Learn. Res., 2025)

PSDNorm: Test-Time Temporal Normalization for Deep Learning on EEG Signals. - Théo Gnassounou; Antoine Collas; Rémi Flamary; Alexandre Gramfort (CoRR, 2025)