Kilian Fatras

According to our database, Kilian Fatras authored at least 23 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

PopulAtion Parameter Averaging (PAPA).

Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien

Trans. Mach. Learn. Res., 2024

Improving and generalizing flow-based generative models with minibatch optimal transport.

Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio

Trans. Mach. Learn. Res., 2024

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation.

Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose

CoRR, 2024

No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths.

Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras, Ioannis Mitliagkas

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SE(3)-Stochastic Flow Matching for Protein Backbone Generation.

Avishek Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees.

Alexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Simulation-Free Schrödinger Bridges via Score and Flow Matching.

Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods.

Tiago Salvador, Kilian Fatras, Ioannis Mitliagkas, Adam M. Oberman

Trans. Mach. Learn. Res., 2023

Unbalanced Optimal Transport meets Sliced-Wasserstein.

Thibault Séjourné, Clément Bonet, Kilian Fatras, Kimia Nadjahi, Nicolas Courty

CoRR, 2023

Diffusion models with location-scale noise.

Alexia Jolicoeur-Martineau, Kilian Fatras, Ke Li, Tal Kachman

CoRR, 2023

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport.

Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio

CoRR, 2023

2022

Generating Natural Adversarial Remote Sensing Images.

Jean-Christophe Burnel, Kilian Fatras, Rémi Flamary, Nicolas Courty

IEEE Trans. Geosci. Remote. Sens., 2022

Wasserstein Adversarial Regularization for Learning With Label Noise.

Kilian Fatras, Bharath Bhushan Damodaran, Sylvain Lobry, Rémi Flamary, Devis Tuia, Nicolas Courty

IEEE Trans. Pattern Anal. Mach. Intell., 2022

On making optimal transport robust to all outliers.

Kilian Fatras

CoRR, 2022

Optimal Transport meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation.

Kilian Fatras, Hiroki Naganuma, Ioannis Mitliagkas

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Deep learning and optimal transport: learning from one another. (Apprentissage profond et transport optimal: apprendre l'un de l'autre).

Kilian Fatras

PhD thesis, 2021

POT: Python Optimal Transport.

Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

J. Mach. Learn. Res., 2021

Minibatch optimal transport distances; analysis and applications.

Kilian Fatras, Younes Zine, Szymon Majewski, Rémi Flamary, Rémi Gribonval, Nicolas Courty

CoRR, 2021

Unbalanced minibatch Optimal Transport; applications to Domain Adaptation.

Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN.

Jean-Christophe Burnel, Kilian Fatras, Nicolas Courty

CoRR, 2020

Learning with minibatch Wasserstein : asymptotic and gradient properties.

Kilian Fatras, Younes Zine, Rémi Flamary, Rémi Gribonval, Nicolas Courty

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise.

Bharath Bhushan Damodaran, Kilian Fatras, Sylvain Lobry, Rémi Flamary, Devis Tuia, Nicolas Courty

CoRR, 2019

Proximal Splitting Meets Variance Reduction.

Fabian Pedregosa, Kilian Fatras, Mattia Casotto

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019