Optimal transport for domain adaptation N Courty, R Flamary, D Tuia, A Rakotomamonjy IEEE transactions on pattern analysis and machine intelligence 39 (9), 1853-1865, 2016 | 1071 | 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 | 834 | 2021 |
Joint distribution optimal transportation for domain adaptation N Courty, R Flamary, A Habrard, A Rakotomamonjy Advances in neural information processing systems 30, 2017 | 619* | 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 | 480 | 2018 |
Optimal transport for structured data with application on graphs V Titouan, N Courty, R Tavenard, R Flamary International Conference on Machine Learning, 6275-6284, 2019 | 268* | 2019 |
Domain adaptation with regularized optimal transport N Courty, R Flamary, D Tuia Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 252 | 2014 |
Large-scale optimal transport and mapping estimation V Seguy, BB Damodaran, R Flamary, N Courty, A Rolet, M Blondel arXiv preprint arXiv:1711.02283, 2017 | 244 | 2017 |
Optimal transport for multi-source domain adaptation under target shift I Redko, N Courty, R Flamary, D Tuia The 22nd International Conference on artificial intelligence and statistics …, 2019 | 170 | 2019 |
Mapping estimation for discrete optimal transport M Perrot, N Courty, R Flamary, A Habrard Advances in Neural Information Processing Systems 29, 2016 | 138 | 2016 |
Wasserstein discriminant analysis R Flamary, M Cuturi, N Courty, A Rakotomamonjy Machine Learning 107, 1923-1945, 2018 | 134 | 2018 |
Unbalanced minibatch optimal transport; applications to domain adaptation K Fatras, T Séjourné, R Flamary, N Courty International Conference on Machine Learning, 3186-3197, 2021 | 133 | 2021 |
Fused Gromov-Wasserstein distance for structured objects T Vayer, L Chapel, R Flamary, R Tavenard, N Courty Algorithms 13 (9), 212, 2020 | 111 | 2020 |
Motion compression using principal geodesics analysis M Tournier, X Wu, N Courty, E Arnaud, L Reveret Computer Graphics Forum 28 (2), 355-364, 2009 | 111 | 2009 |
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 | 107 | 2015 |
The SignCom system for data-driven animation of interactive virtual signers: Methodology and Evaluation S Gibet, N Courty, K Duarte, TL Naour ACM Transactions on Interactive Intelligent Systems (TiiS) 1 (1), 1-23, 2011 | 92 | 2011 |
Learning with minibatch Wasserstein: asymptotic and gradient properties K Fatras, Y Zine, R Flamary, R Gribonval, N Courty arXiv preprint arXiv:1910.04091, 2019 | 81 | 2019 |
Crowd motion capture N Courty, T Corpetti Computer Animation and Virtual Worlds 18 (4‐5), 361-370, 2007 | 81 | 2007 |
Sliced gromov-wasserstein T Vayer, R Flamary, R Tavenard, L Chapel, N Courty arXiv preprint arXiv:1905.10124, 2019 | 79 | 2019 |
Sparse Hilbert Schmidt independence criterion and surrogate-kernel-based feature selection for hyperspectral image classification BB Damodaran, N Courty, S Lefèvre IEEE Transactions on Geoscience and Remote Sensing 55 (4), 2385-2398, 2017 | 77 | 2017 |
End-to-end learned early classification of time series for in-season crop type mapping M Rußwurm, N Courty, R Emonet, S Lefèvre, D Tuia, R Tavenard ISPRS Journal of Photogrammetry and Remote Sensing 196, 445-456, 2023 | 72* | 2023 |