Proximal Splitting Meets Variance Reduction. - Fabian Pedregosa; Kilian Fatras; Mattia Casotto (AISTATS, 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)

Learning with minibatch Wasserstein : asymptotic and gradient properties. - Kilian Fatras; Younes Zine; Rémi Flamary; Rémi Gribonval; Nicolas Courty (AISTATS, 2020)

Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN. - Jean-Christophe Burnel; Kilian Fatras; Nicolas Courty (CoRR, 2020)

Unbalanced minibatch Optimal Transport; applications to Domain Adaptation. - Kilian Fatras; Thibault Séjourné; Rémi Flamary; Nicolas Courty (ICML, 2021)

Minibatch optimal transport distances; analysis and applications. - Kilian Fatras; Younes Zine; Szymon Majewski; Rémi Flamary; Rémi Gribonval; Nicolas Courty (CoRR, 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; et al. (J. Mach. Learn. Res., 2021)

Deep learning and optimal transport: learning from one another. (Apprentissage profond et transport optimal: apprendre l'un de l'autre). - Kilian Fatras (2021)

Optimal Transport meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation. - Kilian Fatras; Hiroki Naganuma; Ioannis Mitliagkas (CoLLAs, 2022)

On making optimal transport robust to all outliers. - Kilian Fatras (CoRR, 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)

Generating Natural Adversarial Remote Sensing Images. - Jean-Christophe Burnel; Kilian Fatras; Rémi Flamary; Nicolas Courty (IEEE Trans. Geosci. Remote. Sens., 2022)

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. - Alexander Tong 001; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Kilian Fatras; Guy Wolf; Yoshua Bengio (CoRR, 2023)

Diffusion models with location-scale noise. - Alexia Jolicoeur-Martineau; Kilian Fatras; Ke Li 011; Tal Kachman (CoRR, 2023)

Unbalanced Optimal Transport meets Sliced-Wasserstein. - Thibault Séjourné; Clément Bonet; Kilian Fatras; Kimia Nadjahi; Nicolas Courty (CoRR, 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)

Simulation-Free Schrödinger Bridges via Score and Flow Matching. - Alexander Tong 001; Nikolay Malkin; Kilian Fatras; Lazar Atanackovic; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Yoshua Bengio (AISTATS, 2024)

Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees. - Alexia Jolicoeur-Martineau; Kilian Fatras; Tal Kachman (AISTATS, 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 001 (ICLR, 2024)

No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths. - Charles Guille-Escuret; Hiroki Naganuma; Kilian Fatras; Ioannis Mitliagkas (ICML, 2024)

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein 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 001; Avishek Joey Bose (NeurIPS, 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 001; Avishek Joey Bose (CoRR, 2024)

Improving and generalizing flow-based generative models with minibatch optimal transport. - Alexander Tong 001; Kilian Fatras; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Guy Wolf; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

PopulAtion Parameter Averaging (PAPA). - Alexia Jolicoeur-Martineau; Emy Gervais; Kilian Fatras; Yan Zhang; Simon Lacoste-Julien (Trans. Mach. Learn. Res., 2024)

Slicing Unbalanced Optimal Transport. - Clément Bonet; Kimia Nadjahi; Thibault Séjourné; Kilian Fatras; Nicolas Courty (Trans. Mach. Learn. Res., 2025)