| Non-linear auto-regressive models for cross-frequency coupling in neural time series T Dupré la Tour, L Tallot, L Grabot, V Doyère, V Van Wassenhove, ... PLoS computational biology 13 (12), e1005893, 2017 | 52* | 2017 |
| Learning the morphology of brain signals using alpha-stable convolutional sparse coding M Jas*, T Dupré la Tour*, U Simsekli, A Gramfort Advances in Neural Information Processing Systems (NeurIPS), 1099-1108, 2017 | 51 | 2017 |
| Multivariate convolutional sparse coding for electromagnetic brain signals T Dupré la Tour*, T Moreau*, M Jas, A Gramfort Advances in Neural Information Processing Systems (NeurIPS), 3292-3302, 2018 | 44 | 2018 |
| The strength of alpha-beta oscillatory coupling predicts motor timing precision L Grabot, TW Kononowicz, T Dupré la Tour, A Gramfort, V Doyère, ... Journal of Neuroscience, 2473-18, 2019 | 21 | 2019 |
| Feature-space selection with banded ridge regression T Dupré la Tour, M Eickenberg, A Nunez-Elizalde, JL Gallant NeuroImage 264, 119728, 2022 | 11 | 2022 |
| scikit-learn/scikit-learn: Scikit-learn 0.22. 1 O Grisel, A Mueller, A Gramfort, G Louppe, P Prettenhofer, M Blondel, ... Zenodo, 2020 | 8 | 2020 |
| Benchopt: Reproducible, efficient and collaborative optimization benchmarks T Moreau, M Massias, A Gramfort, P Ablin, PA Charlier, M Dagréou, ... Advances in Neural Information Processing Systems (NeurIPS), 2022 | 6 | 2022 |
| Non-linear models for neurophysiological time series T Dupré la Tour Université Paris-Saclay, 2018 | 5* | 2018 |
| A finer mapping of convolutional neural network layers to the visual cortex T Dupré la Tour, M Lu, M Eickenberg, JL Gallant Advances in Neural Information Processing Systems (NeurIPS), SVRHM Workshop, 2021 | 4* | 2021 |
| Parametric estimation of spectrum driven by an exogenous signal T Dupré la Tour, Y Grenier, A Gramfort 42nd IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 4 | 2017 |
| Gallant Lab Natural Short Clips 3T fMRI Data AG Huth, S Nishimoto, AT Vu, T Dupré la Tour, JL Gallant | 3 | 2022 |
| Driver estimation in non-linear autoregressive models T Dupré la Tour, Y Grenier, A Gramfort 43nd IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 3 | 2018 |
| The Cortical Representation of Language Timescales is Shared between Reading and Listening C Chen, T Dupré la Tour, J Gallant, D Klein, F Deniz bioRxiv, 2023 | | 2023 |
| Dynamic, naturalistic faces embedded in a narrative elicit responses in the distributed face processing system V Chauhan, R Philip, MV di Oleggio Castello, G Jiahui, M Feilong, ... Journal of Vision 22 (14), 4386-4386, 2022 | | 2022 |
| Long-term recordings from area V4 neurons and an accurately-predicting deep convolutional energy model reveal spatial, chromatic and temporal tuning properties under … M Winter*, T Dupré la Tour*, M Eickenberg*, M Oliver*, J Gallant Journal of Vision 22 (14), 4363-4363, 2022 | | 2022 |
| Pymoten: scientific python package for computing motion energy features from video NE Anwar O., F Deniz, T Dupré la Tour, M Visconti di Oleggio Castello, ... Zenodo. https://zenodo.org/record/6349625, 2022 | | 2022 |
| Parametric models of phase-amplitude coupling in neural time series T Dupré la Tour, Y Grenier, A Gramfort International Biomedical and Astronomical Signal Processing (BASP) Frontiers …, 2017 | | 2017 |
| scikit-learn/scikit-learn: scikit-learn 1.1. 1 O Grisel, A Mueller, A Gramfort, G Louppe, P Prettenhofer, M Blondel, ... Zenodo, 0 | | |
Alexandre GramfortMetaVerified email at meta.com
