Kilian Fatras
Kilian Fatras
PostDoctoral Fellow at Mila Québec AI Institute
Verified email at - Homepage
Cited by
Cited by
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
Unbalanced minibatch optimal transport; applications to domain adaptation
K Fatras, T Séjourné, N Courty, R Flamary
International Conference on Machine Learning, 3186-3197, 2021
Learning with minibatch Wasserstein: asymptotic and gradient properties
K Fatras, Y Zine, R Flamary, R Gribonval, N Courty
the 23nd International Conference on Artificial Intelligence and Statistics 108, 2020
Improving and generalizing flow-based generative models with minibatch optimal transport
A Tong, N Malkin, G Huguet, Y Zhang, J Rector-Brooks, K Fatras, G Wolf, ...
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023
Minibatch optimal transport distances; analysis and applications
K Fatras, Y Zine, S Majewski, R Flamary, R Gribonval, N Courty
arXiv preprint arXiv:2101.01792, 2021
Wasserstein adversarial regularization for learning with label noise
K Fatras, BB Damodaran, S Lobry, R Flamary, D Tuia, N Courty
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 7296 …, 2021
Generating natural adversarial Remote Sensing Images
JC Burnel, K Fatras, R Flamary, N Courty
IEEE Transactions on Geoscience and Remote Sensing 60, 1-14, 2021
Proximal Splitting Meets Variance Reduction
F Pedregosa, K Fatras, M Casotto
The 22nd International Conference on Artificial Intelligence and Statistics …, 2018
Simulation-free Schrödinger bridges via score and flow matching
A Tong*, N Malkin*, K Fatras*, L Atanackovic, Y Zhang, G Huguet, G Wolf, ...
arXiv preprint arXiv:2307.03672, 2023
Unbalanced Optimal Transport meets Sliced-Wasserstein
T Séjourné, C Bonet, K Fatras, K Nadjahi, N Courty
arXiv preprint arXiv:2306.07176, 2023
PopulAtion Parameter Averaging (PAPA)
A Jolicoeur-Martineau, E Gervais, K Fatras, Y Zhang, S Lacoste-Julien
arXiv preprint arXiv:2304.03094, 2023
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods
T Salvador*, K Fatras*, I Mitliagkas, A Oberman
TMLR, 2022
Optimal transport meets noisy label robust loss and MixUp regularization for domain adaptation
K Fatras, H Naganuma, I Mitliagkas
Conference on Lifelong Learning Agents, 966-981, 2022
Deep learning and optimal transport: learning from one another
K Fatras
Université de Bretagne Sud, 2021
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
AJ Bose, T Akhound-Sadegh, K Fatras, G Huguet, J Rector-Brooks, ...
arXiv preprint arXiv:2310.02391, 2023
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
A Jolicoeur-Martineau, K Fatras, T Kachman
arXiv preprint arXiv:2309.09968, 2023
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
C Guille-Escuret, H Naganuma, K Fatras, I Mitliagkas
arXiv preprint arXiv:2306.11922, 2023
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