Rémi Flamary
Rémi Flamary
CMAP, École Polytechnique, Institut Polytechnique de Paris
Verified email at - Homepage
Cited by
Cited by
Joint distribution optimal transportation for domain adaptation
N Courty, R Flamary, A Habrard, A Rakotomamonjy
Advances in Neural Information Processing Systems, 3730-3739, 2017
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
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
Domain adaptation with regularized optimal transport
N Courty, R Flamary, D Tuia
Machine Learning and Knowledge Discovery in Databases: European Conference …, 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
Optimal Transport for structured data with application on graphs
T Vayer, N Courty, R Tavenard, R Flamary
International Conference on Machine Learning, 6275-6284, 2019
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
Mapping estimation for discrete optimal transport
M Perrot, N Courty, R Flamary, A Habrard
Advances in Neural Information Processing Systems 29, 2016
Wasserstein discriminant analysis
R Flamary, M Cuturi, N Courty, A Rakotomamonjy
Machine Learning, 2018
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
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
The strong gravitational lens finding challenge
RB Metcalf, M Meneghetti, C Avestruz, F Bellagamba, CR Bom, E Bertin, ...
Astronomy & Astrophysics 625, A119, 2019
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
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
Sliced Gromov-Wasserstein
T Vayer, R Flamary, R Tavenard, L Chapel, N Courty
Neural Information Processing Systems (NeurIPS), 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
Decoding finger movements from ECoG signals using switching linear models
R Flamary, A Rakotomamonjy
Frontiers in Neuroscience 6 (29), 2012
Fused Gromov-Wasserstein distance for structured objects
T Vayer, L Chapel, R Flamary, R Tavenard, N Courty
Algorithms 13 (9), 212, 2020
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
sw-SVM: sensor weighting support vector machines for EEG-based brain–computer interfaces
N Jrad, M Congedo, R Phlypo, S Rousseau, R Flamary, F Yger, ...
Journal of neural engineering 8 (5), 056004, 2011
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