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Kilian Fatras
Kilian Fatras
Machine Learning research scientist
Adresse e-mail validée de mila.quebec - Page d'accueil
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Année
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
8282021
Unbalanced minibatch optimal transport; applications to domain adaptation
K Fatras, T Séjourné, N Courty, R Flamary
International Conference on Machine Learning, 3186-3197, 2021
1322021
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
792020
Improving and generalizing flow-based generative models with minibatch optimal transport
A Tong*, K Fatras*, N Malkin*, G Huguet, Y Zhang, J Rector-Brooks, ...
TMLR, 2023
74*2023
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
37*2021
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
372021
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
17*2021
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
AJ Bose, T Akhound-Sadegh, K Fatras, G Huguet, J Rector-Brooks, ...
ICLR, 2024
142024
Simulation-free Schrödinger bridges via score and flow matching
A Tong*, N Malkin*, K Fatras*, L Atanackovic, Y Zhang, G Huguet, G Wolf, ...
AISTATS, 2024
142024
Proximal Splitting Meets Variance Reduction
F Pedregosa, K Fatras, M Casotto
The 22nd International Conference on Artificial Intelligence and Statistics …, 2018
142018
Population parameter averaging (papa)
A Jolicoeur-Martineau, E Gervais, K Fatras, Y Zhang, S Lacoste-Julien
TMLR, 2023
82023
Unbalanced optimal transport meets sliced-Wasserstein
T Séjourné, C Bonet, K Fatras, K Nadjahi, N Courty
arXiv preprint arXiv:2306.07176, 2023
72023
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
A Jolicoeur-Martineau, K Fatras, T Kachman
AISTATS, 2024
52024
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
52022
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods
T Salvador*, K Fatras*, I Mitliagkas, A Oberman
TMLR, 2023
42023
Diffusion models with location-scale noise
A Jolicoeur-Martineau, K Fatras, K Li, T Kachman
arXiv preprint arXiv:2304.05907, 2023
22023
Deep learning and optimal transport: learning from one another
K Fatras
Université de Bretagne Sud, 2021
22021
Sequence-Augmented SE (3)-Flow Matching For Conditional Protein Backbone Generation
G Huguet, J Vuckovic, K Fatras, E Thibodeau-Laufer, P Lemos, R Islam, ...
arXiv preprint arXiv:2405.20313, 2024
2024
Scalable Unbalanced Optimal Transport by Slicing
K Nadjahi, K Fatras, N Courty
2024
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
C Guille-Escuret, H Naganuma, K Fatras, I Mitliagkas
ICML, 2024
2024
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