| Optimal transport for domain adaptation N Courty, R Flamary, D Tuia, A Rakotomamonjy IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 | 1278 | 2016 |
| POT: Python Optimal Transport R Flamary, N Courty, A Gramfort, MZ Alaya, A Boisbunon, S Chambon, ... Journal of Machine Learning Research 22 (78), 1-8, 2021 | 1048 | 2021 |
| Joint distribution optimal transportation for domain adaptation N Courty, R Flamary, A Habrard, A Rakotomamonjy Advances in Neural Information Processing Systems, 3730-3739, 2017 | 639 | 2017 |
| Deepjdot: Deep joint distribution optimal transport for unsupervised domain adaptation BB Damodaran, B Kellenberger, R Flamary, D Tuia, N Courty Proceedings of the European conference on computer vision (ECCV), 447-463, 2018 | 549 | 2018 |
| Optimal Transport for structured data with application on graphs T Vayer, L Chapel, R Flamary, R Tavenard, N Courty International Conference on Machine Learning, 6275-6284, 2019 | 313* | 2019 |
| Domain adaptation with regularized optimal transport N Courty, R Flamary, D Tuia Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 275 | 2014 |
| Large-Scale Optimal Transport and Mapping Estimation V Seguy, BB Damodaran, R Flamary, N Courty, A Rolet, M Blondel International Conference on Learning Representations (ICLR), 2018 | 270 | 2018 |
| Optimal transport for multi-source domain adaptation under target shift I Redko, N Courty, R Flamary, D Tuia International Conference on Artificial Intelligence and Statistics (AISTAT), 2019 | 183 | 2019 |
| Unbalanced minibatch optimal transport; applications to domain adaptation K Fatras, T Séjourné, R Flamary, N Courty International Conference on Machine Learning, 3186-3197, 2021 | 166 | 2021 |
| The strong gravitational lens finding challenge RB Metcalf, M Meneghetti, C Avestruz, F Bellagamba, CR Bom, E Bertin, ... Astronomy & Astrophysics 625, A119, 2019 | 150 | 2019 |
| Mapping estimation for discrete optimal transport M Perrot, N Courty, R Flamary, A Habrard Advances in Neural Information Processing Systems 29, 2016 | 144 | 2016 |
| Fused Gromov-Wasserstein distance for structured objects T Vayer, L Chapel, R Flamary, R Tavenard, N Courty Algorithms 13 (9), 212, 2020 | 140 | 2020 |
| Wasserstein discriminant analysis R Flamary, M Cuturi, N Courty, A Rakotomamonjy Machine Learning, 2018 | 140 | 2018 |
| Sliced Gromov-Wasserstein T Vayer, R Flamary, R Tavenard, L Chapel, N Courty Neural Information Processing Systems (NeurIPS), 2019 | 122* | 2019 |
| Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM L Laporte, R Flamary, S Canu, S Déjean, J Mothe IEEE transactions on Neural Networks and Learning Systems 25 (6), 1118 - 1130, 2014 | 112 | 2014 |
| Multiclass feature learning for hyperspectral image classification: Sparse and hierarchical solutions D Tuia, R Flamary, N Courty ISPRS Journal of Photogrammetry and Remote Sensing 105, 272-285, 2015 | 108 | 2015 |
| lp-lq penalty for sparse linear and sparse multiple kernel multi-task learning A Rakotomamonjy, R Flamary, G Gasso, S Canu IEEE Transactions on Neural Networks 22 (8), 1307-1320, 2011 | 98 | 2011 |
| Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM D Tuia, M Volpi, M Dalla Mura, A Rakotomamonjy, R Flamary IEEE Transactions on Geoscience and Remote Sensing, 1-13, 2014 | 97 | 2014 |
| Learning with minibatch Wasserstein: asymptotic and gradient properties K Fatras, Y Zine, R Flamary, R Gribonval, N Courty International Conference on Artificial Intelligence and Statistics (AISTAT), 2020 | 96 | 2020 |
| Decoding finger movements from ECoG signals using switching linear models R Flamary, A Rakotomamonjy Frontiers in Neuroscience 6 (29), 2012 | 86 | 2012 |
Nicolas CourtyFull Professor, Université Bretagne Sud, laboratoire IRISA在 univ-ubs.fr 的电子邮件经过验证
