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Kilian Fatras
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2020 – today
- 2024
- [j6]Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio:
Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. 2024 (2024) - [j5]Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien:
PopulAtion Parameter Averaging (PAPA). Trans. Mach. Learn. Res. 2024 (2024) - [c8]Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio:
Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS 2024: 1279-1287 - [c7]Alexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman:
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees. AISTATS 2024: 1288-1296 - [c6]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:
SE(3)-Stochastic Flow Matching for Protein Backbone Generation. ICLR 2024 - [c5]Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras, Ioannis Mitliagkas:
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths. ICML 2024 - [i17]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:
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. CoRR abs/2405.20313 (2024) - 2023
- [j4]Tiago Salvador, Kilian Fatras, Ioannis Mitliagkas, Adam M. Oberman:
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods. Trans. Mach. Learn. Res. 2023 (2023) - [i16]Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio:
Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. CoRR abs/2302.00482 (2023) - [i15]Alexia Jolicoeur-Martineau, Emy Gervais, Kilian Fatras, Yan Zhang, Simon Lacoste-Julien:
PopulAtion Parameter Averaging (PAPA). CoRR abs/2304.03094 (2023) - [i14]Alexia Jolicoeur-Martineau, Kilian Fatras, Ke Li, Tal Kachman:
Diffusion models with location-scale noise. CoRR abs/2304.05907 (2023) - [i13]Thibault Séjourné, Clément Bonet, Kilian Fatras, Kimia Nadjahi, Nicolas Courty:
Unbalanced Optimal Transport meets Sliced-Wasserstein. CoRR abs/2306.07176 (2023) - [i12]Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras, Ioannis Mitliagkas:
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths. CoRR abs/2306.11922 (2023) - [i11]Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio:
Simulation-free Schrödinger bridges via score and flow matching. CoRR abs/2307.03672 (2023) - [i10]Alexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman:
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees. CoRR abs/2309.09968 (2023) - [i9]Avishek Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong:
SE(3)-Stochastic Flow Matching for Protein Backbone Generation. CoRR abs/2310.02391 (2023) - 2022
- [j3]Kilian Fatras, Bharath Bhushan Damodaran, Sylvain Lobry, Rémi Flamary, Devis Tuia, Nicolas Courty:
Wasserstein Adversarial Regularization for Learning With Label Noise. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 7296-7306 (2022) - [j2]Jean-Christophe Burnel, Kilian Fatras, Rémi Flamary, Nicolas Courty:
Generating Natural Adversarial Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - [c4]Kilian Fatras, Hiroki Naganuma, Ioannis Mitliagkas:
Optimal Transport meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation. CoLLAs 2022: 966-981 - [i8]Kilian Fatras, Hiroki Naganuma, Ioannis Mitliagkas:
Optimal transport meets noisy label robust loss and MixUp regularization for domain adaptation. CoRR abs/2206.11180 (2022) - [i7]Kilian Fatras:
On making optimal transport robust to all outliers. CoRR abs/2206.11988 (2022) - [i6]Tiago Salvador, Kilian Fatras, Ioannis Mitliagkas, Adam M. Oberman:
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods. CoRR abs/2210.01210 (2022) - 2021
- [b1]Kilian Fatras:
Deep learning and optimal transport: learning from one another. (Apprentissage profond et transport optimal: apprendre l'un de l'autre). University of Southern Brittany, Vannes, Morbihan, France, 2021 - [j1]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:
POT: Python Optimal Transport. J. Mach. Learn. Res. 22: 78:1-78:8 (2021) - [c3]Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty:
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation. ICML 2021: 3186-3197 - [i5]Kilian Fatras, Younes Zine, Szymon Majewski, Rémi Flamary, Rémi Gribonval, Nicolas Courty:
Minibatch optimal transport distances; analysis and applications. CoRR abs/2101.01792 (2021) - [i4]Kilian Fatras, Thibault Séjourné, Nicolas Courty, Rémi Flamary:
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation. CoRR abs/2103.03606 (2021) - 2020
- [c2]Kilian Fatras, Younes Zine, Rémi Flamary, Rémi Gribonval, Nicolas Courty:
Learning with minibatch Wasserstein : asymptotic and gradient properties. AISTATS 2020: 2131-2141 - [i3]Jean-Christophe Burnel, Kilian Fatras, Nicolas Courty:
Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN. CoRR abs/2001.09993 (2020)
2010 – 2019
- 2019
- [c1]Fabian Pedregosa, Kilian Fatras, Mattia Casotto:
Proximal Splitting Meets Variance Reduction. AISTATS 2019: 1-10 - [i2]Bharath Bhushan Damodaran, Kilian Fatras, Sylvain Lobry, Rémi Flamary, Devis Tuia, Nicolas Courty:
Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise. CoRR abs/1904.03936 (2019) - [i1]Kilian Fatras, Younes Zine, Rémi Flamary, Rémi Gribonval, Nicolas Courty:
Learning with minibatch Wasserstein : asymptotic and gradient properties. CoRR abs/1910.04091 (2019)
Coauthor Index
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last updated on 2024-11-19 21:46 CET by the dblp team
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