‪Théo Uscidda‬ - ‪Google Scholar‬

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202320249 3

Co-authors

Marco CuturiApple / CREST-ENSAE.Verified email at apple.com
Fabian J TheisHelmholtz Munich, Technical University of MunichVerified email at helmholtz-muenchen.de
Dominik KleinHelmholtz Center MunichVerified email at helmholtz-munich.de
Luca EyringELLIS, University of TübingenVerified email at uni-tuebingen.de
Zeynep AkataProfessor at TUM and Director at Helmholtz MunichVerified email at helmholtz-munich.de

Théo Uscidda

Théo Uscidda

CREST - ENSAE

Verified email at ensae.fr - Homepage

Optimal Transport Generative Modeling


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The monge gap: A regularizer to learn all transport maps T Uscidda, M Cuturi International Conference on Machine Learning, 34709-34733, 2023	12	2023
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation L Eyring, D Klein, T Uscidda, G Palla, N Kilbertus, Z Akata, F Theis arXiv preprint arXiv:2311.15100, 2023		2023
Generative Entropic Neural Optimal Transport To Map Within and Across Spaces D Klein, T Uscidda, F Theis, M Cuturi arXiv preprint arXiv:2310.09254, 2023		2023

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Articles 1–3