PopulAtion Parameter Averaging (PAPA).
Trans. Mach. Learn. Res., 2024
Improving and generalizing flow-based generative models with minibatch optimal transport.
Trans. Mach. Learn. Res., 2024
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation.
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CoRR, 2024
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation.
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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
SE(3)-Stochastic Flow Matching for Protein Backbone Generation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Simulation-Free Schrödinger Bridges via Score and Flow Matching.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods.
Trans. Mach. Learn. Res., 2023
Unbalanced Optimal Transport meets Sliced-Wasserstein.
CoRR, 2023
Diffusion models with location-scale noise.
CoRR, 2023
Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport.
CoRR, 2023
Generating Natural Adversarial Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2022
Wasserstein Adversarial Regularization for Learning With Label Noise.
IEEE Trans. Pattern Anal. Mach. Intell., 2022
On making optimal transport robust to all outliers.
CoRR, 2022
Optimal Transport meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation.
Proceedings of the Conference on Lifelong Learning Agents, 2022
Deep learning and optimal transport: learning from one another. (Apprentissage profond et transport optimal: apprendre l'un de l'autre).
PhD thesis, 2021
Minibatch optimal transport distances; analysis and applications.
CoRR, 2021
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation.
Proceedings of the 38th International Conference on Machine Learning, 2021
Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN.
CoRR, 2020
Learning with minibatch Wasserstein : asymptotic and gradient properties.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise.
CoRR, 2019
Proximal Splitting Meets Variance Reduction.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019