Optimizing deep video representation to match brain activity. - Hugo Richard; Ana Luísa Pinho; Bertrand Thirion; Guillaume Charpiat (CoRR, 2018)

Local Optimal Transport for Functional Brain Template Estimation. - Thomas Bazeille; Hugo Richard; Hicham Janati; Bertrand Thirion (IPMI, 2019)

Fast shared response model for fMRI data. - Hugo Richard; Lucas Martin; Ana Luísa Pinho; Jonathan W. Pillow; Bertrand Thirion (CoRR, 2019)

Modeling Shared responses in Neuroimaging Studies through MultiView ICA. - Hugo Richard; Luigi Gresele; Aapo Hyvärinen; Bertrand Thirion; Alexandre Gramfort; Pierre Ablin (NeurIPS, 2020)

Detecting Dyslexia from Audio Records: An AI Approach. - Jim Radford; Gilles Richard; Hugo Richard; Mathieu Serrurier (HEALTHINF, 2021)

Functional Magnetic Resonance Imaging Data Augmentation Through Conditional ICA. - Badr Tajini; Hugo Richard; Bertrand Thirion (MICCAI (2), 2021)

Shared Independent Component Analysis for Multi-Subject Neuroimaging. - Hugo Richard; Pierre Ablin; Bertrand Thirion; Alexandre Gramfort; Aapo Hyvärinen (NeurIPS, 2021)

Adaptive Multi-View ICA: Estimation of noise levels for optimal inference. - Hugo Richard; Pierre Ablin; Aapo Hyvärinen; Alexandre Gramfort; Bertrand Thirion (CoRR, 2021)

mvlearn: Multiview Machine Learning in Python. - Ronan Perry; Gavin Mischler; Richard Guo; Theo Lee; Alexander Chang; Arman Koul; Cameron Franz; Hugo Richard; Iain Carmichael; Pierre Ablin; Alexandre Gramfort; Joshua T. Vogelstein (J. Mach. Learn. Res., 2021)

An empirical evaluation of functional alignment using inter-subject decoding. - Thomas Bazeille; Elizabeth Dupre; Hugo Richard; Jean-Baptiste Poline; Bertrand Thirion (NeuroImage, 2021)

Brain topography beyond parcellations: Local gradients of functional maps. - Elvis Dohmatob; Hugo Richard; Ana Luísa Pinho; Bertrand Thirion (NeuroImage, 2021)

Unsupervised component analysis for neuroimaging data. (Analyse non-supervisée en composante de données d'imageries neuronales). - Hugo Richard (2021)

Static Scheduling with Predictions Learned through Efficient Exploration. - Hugo Richard; Flore Sentenac; Corentin Odic; Mathieu Molina; Vianney Perchet (CoRR, 2022)

On Preemption and Learning in Stochastic Scheduling. - Nadav Merlis; Hugo Richard; Flore Sentenac; Corentin Odic; Mathieu Molina; Vianney Perchet (ICML, 2023)

Constant or logarithmic regret in asynchronous multiplayer bandits. - Hugo Richard; Etienne Boursier; Vianney Perchet (CoRR, 2023)

Multi-armed bandits with guaranteed revenue per arm. - Dorian Baudry; Nadav Merlis; Mathieu Benjamin Molina; Hugo Richard; Vianney Perchet (AISTATS, 2024)

Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication. - Hugo Richard; Etienne Boursier; Vianney Perchet (AISTATS, 2024)

Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits. - Dorian Baudry; Hugo Richard; Maria Cherifa; Vianney Perchet; Clément Calauzènes (NeurIPS, 2024)

Improved learning rates in multi-unit uniform price auctions. - Marius Potfer; Dorian Baudry; Hugo Richard; Vianney Perchet; Cheng Wan (NeurIPS, 2024)

Open Research Challenges for Private Advertising Systems Under Local Differential Privacy. - Matilde Tullii; Solenne Gaucher; Hugo Richard; Eustache Diemert; Vianney Perchet; Alain Rakotomamonjy; Clément Calauzènes; Maxime Vono (WISE (5), 2024)

Distribution-Aware Mean Estimation under User-level Local Differential Privacy. - Corentin Pla; Maxime Vono; Hugo Richard (AISTATS, 2025)