Parametric estimation of spectrum driven by an exogenous signal. - Tom Dupré la Tour; Yves Grenier; Alexandre Gramfort (ICASSP, 2017)

Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding. - Mainak Jas; Tom Dupré la Tour; Umut Simsekli; Alexandre Gramfort (NIPS, 2017)

Non-linear auto-regressive models for cross-frequency coupling in neural time series. - Tom Dupré la Tour; Lucille Tallot; Laetitia Grabot; Valérie Doyère; Virginie van Wassenhove; Yves Grenier; Alexandre Gramfort (PLoS Comput. Biol., 2017)

Driver Estimation in Non-Linear Autoregressive Models. - Tom Dupré la Tour; Yves Grenier; Alexandre Gramfort (ICASSP, 2018)

Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals. - Tom Dupré la Tour; Thomas Moreau 001; Mainak Jas; Alexandre Gramfort (NeurIPS, 2018)

Nonlinear models for neurophysiological time series. (Modèles non linéaires pour les séries temporelles neurophysiologiques). - Tom Dupré la Tour (2018)

Benchopt: Reproducible, efficient and collaborative optimization benchmarks. - Thomas Moreau 001; Mathurin Massias; Alexandre Gramfort; Pierre Ablin; Pierre-Antoine Bannier; Benjamin Charlier; Mathieu Dagréou; Tom Dupré la Tour; Ghislain Durif; Cássio F. Dantas; Quentin Klopfenstein; Johan Larsson 002; et al. (NeurIPS, 2022)

Feature-space selection with banded ridge regression. - Tom Dupré la Tour; Michael Eickenberg; Anwar Nunez-Elizalde; Jack L. Gallant (NeuroImage, 2022)

Scaling and evaluating sparse autoencoders. - Leo Gao; Tom Dupré la Tour; Henk Tillman; Gabriel Goh; Rajan Troll; Alec Radford; Ilya Sutskever; Jan Leike; Jeffrey Wu 003 (ICLR, 2025)

Persona Features Control Emergent Misalignment. - Miles Wang; Tom Dupré la Tour; Olivia Watkins; Alex Makelov; Ryan A. Chi; Samuel Miserendino; Johannes Heidecke; Tejal Patwardhan; Dan Mossing (CoRR, 2025)