| Which fMRI clustering gives good brain parcellations? B Thirion, G Varoquaux, E Dohmatob, JB Poline Frontiers in neuroscience 8, 167, 2014 | 275 | 2014 |
| Extracting brain regions from rest fMRI with total-variation constrained dictionary learning A Abraham, E Dohmatob, B Thirion, D Samaras, G Varoquaux International conference on medical image computing and computer-assisted …, 2013 | 60 | 2013 |
| Dark control: The default mode network as a reinforcement learning agent E Dohmatob, G Dumas, D Bzdok Human Brain Mapping 41 (12), 3318-3341, 2020 | 49* | 2020 |
| Benchmarking solvers for TV-ℓ1least-squares and logistic regression in brain imaging ED Dohmatob, A Gramfort, B Thirion, G Varoquaux 2014 International Workshop on Pattern Recognition in Neuroimaging, 1-4, 2014 | 37 | 2014 |
| Generalized no free lunch theorem for adversarial robustness E Dohmatob arXiv preprint arXiv:1810.04065, 2018 | 36* | 2018 |
| Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping AL Pinho, A Amadon, T Ruest, M Fabre, E Dohmatob, I Denghien, ... Scientific data 5 (1), 1-15, 2018 | 29 | 2018 |
| Learning brain regions via large-scale online structured sparse dictionary-learning E Dohmatob, A Mensch, G Varoquaux, B Thirion Neural Information Processing Systems (NIPS), 2016 | 20 | 2016 |
| Distributionally robust reinforcement learning E Smirnova, E Dohmatob, J Mary arXiv preprint arXiv:1902.08708, 2019 | 18 | 2019 |
| Inter-subject registration of functional images: do we need anatomical images? E Dohmatob, G Varoquaux, B Thirion Frontiers in neuroscience 12, 64, 2018 | 14 | 2018 |
| Integrating multimodal priors in predictive models for the functional characterization of Alzheimer’s disease M Rahim, B Thirion, A Abraham, M Eickenberg, E Dohmatob, C Comtat, ... International Conference on Medical Image Computing and Computer-Assisted …, 2015 | 14 | 2015 |
| L'intonation et ses fonctions syntaxiques en rifain MB Lafkioui Articles de linguistique berbère. Mémorial Werner Vycichl., 253-281, 2002 | 14 | 2002 |
| Learning nonsymmetric determinantal point processes M Gartrell, VE Brunel, E Dohmatob, S Krichene arXiv preprint arXiv:1905.12962, 2019 | 13 | 2019 |
| Grouping total variation and sparsity: Statistical learning with segmenting penalties M Eickenberg, E Dohmatob, B Thirion, G Varoquaux International Conference on Medical Image Computing and Computer-Assisted …, 2015 | 13 | 2015 |
| FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging G Varoquaux, M Eickenberg, E Dohmatob, B Thirion arXiv preprint arXiv:1512.06999, 2015 | 9 | 2015 |
| Speeding-up model-selection in GraphNet via early-stopping and univariate feature-screening E Dohmatob, M Eickenberg, B Thirion, G Varoquaux 2015 International Workshop on Pattern Recognition in NeuroImaging, 17-20, 2015 | 9 | 2015 |
| Which fMRI clustering gives good brain parcellations? Front. Neurosci. 8: 167 B Thirion, G Varoquaux, E Dohmatob, JB Poline | 9 | 2014 |
| Adversarial robustness via adversarial label-smoothing M Goibert, E Dohmatob | 8* | 2019 |
| Region segmentation for sparse decompositions: better brain parcellations from rest fMRI A Abraham, E Dohmatob, B Thirion, D Samaras, G Varoquaux arXiv preprint arXiv:1412.3925, 2014 | 8 | 2014 |
| Multivariate Hurst exponent estimation in fMRI. Application to brain decoding of perceptual learning H Pellé, P Ciuciu, M Rahim, E Dohmatob, P Abry, V Van Wassenhove 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 996-1000, 2016 | 6 | 2016 |
| Total variation meets sparsity: statistical learning with segmenting penalties M Eickenberg, E Dohmatob, B Thirion, G Varoquaux Medical Image Computing and Computer Aided Intervention (MICCAI), 2015 | 6 | 2015 |
Gaël VaroquauxResearch director, INRIAAdresse e-mail validée de normalesup.org
