| Machine learning for neuroimaging with scikit-learn A Abraham, F Pedregosa, M Eickenberg, P Gervais, A Mueller, J Kossaifi, ... Frontiers in neuroinformatics 8, 14, 2014 | 1604 | 2014 |
| Seeing it all: Convolutional network layers map the function of the human visual system M Eickenberg, A Gramfort, G Varoquaux, B Thirion NeuroImage 152, 184-194, 2017 | 345 | 2017 |
| Greedy Layerwise Learning Can Scale to ImageNet E Belilovsky, M Eickenberg, E Oyallon arXiv preprint arXiv:1812.11446, 2018 | 160 | 2018 |
| Kymatio: Scattering Transforms in Python M Andreux, T Angles, G Exarchakis, R Leonarduzzi, G Rochette, L Thiry, ... arXiv preprint arXiv:1812.11214, 2018 | 138 | 2018 |
| Decoupled Greedy Learning of CNNs E Belilovsky, M Eickenberg, E Oyallon arXiv preprint arXiv:1901.08164, 2019 | 87 | 2019 |
| Solid harmonic wavelet scattering for predictions of molecule properties M Eickenberg, G Exarchakis, M Hirn, S Mallat, L Thiry The Journal of Chemical Physics 148 (24), 241732, 2018 | 79 | 2018 |
| Formal models of the network co-occurrence underlying mental operations D Bzdok, G Varoquaux, O Grisel, M Eickenberg, C Poupon, B Thirion PLoS computational biology 12 (6), e1004994, 2016 | 73 | 2016 |
| Data-driven HRF estimation for encoding and decoding models F Pedregosa, M Eickenberg, P Ciuciu, B Thirion, A Gramfort NeuroImage 104, 209-220, 2015 | 72 | 2015 |
| Solid harmonic wavelet scattering: Predicting quantum molecular energy from invariant descriptors of 3D electronic densities M Eickenberg, G Exarchakis, M Hirn, S Mallat Advances in Neural Information Processing Systems, 6540-6549, 2017 | 59 | 2017 |
| The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence F Villaescusa-Navarro, S Genel, D Angles-Alcazar, L Thiele, R Dave, ... arXiv preprint arXiv:2109.10915, 2021 | 53 | 2021 |
| Semi-supervised factored logistic regression for high-dimensional neuroimaging data D Bzdok, M Eickenberg, O Grisel, B Thirion, G Varoquaux Advances in neural information processing systems, 3348-3356, 2015 | 45 | 2015 |
| Feature-space selection with banded ridge regression TD la Tour, M Eickenberg, JL Gallant bioRxiv, 2022 | 27 | 2022 |
| Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging O Benkarim, C Paquola, B Park, V Kebets, SJ Hong, R Vos de Wael, ... PLoS biology 20 (4), e3001627, 2022 | 25* | 2022 |
| 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 | 23* | 2015 |
| Characterizing responses of translation-invariant neurons to natural stimuli: Maximally informative invariant dimensions M Eickenberg, RJ Rowekamp, M Kouh, TO Sharpee Neural computation 24 (9), 2384-2421, 2012 | 21 | 2012 |
| Parametric Scattering Networks S Gauthier, B Thérien, L Alsène-Racicot, I Rish, E Belilovsky, ... arXiv preprint arXiv:2107.09539, 2021 | 17 | 2021 |
| 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 | 16 | 2015 |
| Polarization of defect related optical transitions in chalcopyrites K Hönes, M Eickenberg, S Siebentritt, C Persson Applied physics letters 93 (9), 092102, 2008 | 16 | 2008 |
| The CAMELS project: public data release F Villaescusa-Navarro, S Genel, D Anglés-Alcázar, LA Perez, ... arXiv preprint arXiv:2201.01300, 2022 | 14 | 2022 |
| Phase retrieval with holography and untrained priors: Tackling the challenges of low-photon nanoscale imaging H Lawrence, DA Barmherzig, H Li, M Eickenberg, M Gabrié arXiv preprint arXiv:2012.07386, 2020 | 14 | 2020 |
