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Meyer Scetbon
Meyer Scetbon
Researcher, Microsoft
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Deep k-svd denoising
M Scetbon, M Elad, P Milanfar
IEEE Transactions on Image Processing 30, 5944-5955, 2021
1192021
Low-rank sinkhorn factorization
M Scetbon, M Cuturi, G Peyré
International Conference on Machine Learning, 9344-9354, 2021
552021
Linear-time gromov wasserstein distances using low rank couplings and costs
M Scetbon, G Peyré, M Cuturi
International Conference on Machine Learning, 19347-19365, 2022
482022
Mixed nash equilibria in the adversarial examples game
L Meunier, M Scetbon, RB Pinot, J Atif, Y Chevaleyre
International Conference on Machine Learning, 7677-7687, 2021
332021
A spectral analysis of dot-product kernels
M Scetbon, Z Harchaoui
International conference on artificial intelligence and statistics, 3394-3402, 2021
272021
Linear time Sinkhorn divergences using positive features
M Scetbon, M Cuturi
Advances in neural information processing systems 33, 13468-13480, 2020
252020
Low-rank optimal transport: Approximation, statistics and debiasing
M Scetbon, M Cuturi
Advances in Neural Information Processing Systems 35, 6802-6814, 2022
182022
Triangular flows for generative modeling: Statistical consistency, smoothness classes, and fast rates
NJ Irons, M Scetbon, S Pal, Z Harchaoui
International Conference on Artificial Intelligence and Statistics, 10161-10195, 2022
152022
Equitable and optimal transport with multiple agents
M Scetbon, L Meunier, J Atif, M Cuturi
International Conference on Artificial Intelligence and Statistics, 2035-2043, 2021
10*2021
Comparing distributions: geometry improves kernel two-sample testing
M Scetbon, G Varoquaux
Advances in Neural Information Processing Systems 32, 2019
10*2019
Harmonic decompositions of convolutional networks
M Scetbon, Z Harchaoui
International Conference on Machine Learning, 8522-8532, 2020
82020
An asymptotic test for conditional independence using analytic kernel embeddings
M Scetbon, L Meunier, Y Romano
International Conference on Machine Learning, 19328-19346, 2022
72022
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
M Scetbon, E Dohmatob
International Conference on Artificial Intelligence and Statistics, 11583-11607, 2023
32023
The Essential Role of Causality in Foundation World Models for Embodied AI
T Gupta, W Gong, C Ma, N Pawlowski, A Hilmkil, M Scetbon, A Famoti, ...
arXiv preprint arXiv:2402.06665, 2024
22024
FiP: a Fixed-Point Approach for Causal Generative Modeling
M Scetbon, J Jennings, A Hilmkil, C Zhang, C Ma
arXiv preprint arXiv:2404.06969, 2024
12024
Unbalanced Low-rank Optimal Transport Solvers
M Scetbon, M Klein, G Palla, M Cuturi
Advances in Neural Information Processing Systems 36, 2024
12024
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms
E Dohmatob, M Scetbon
arXiv preprint arXiv:2308.00556, 2023
12023
Polynomial-Time Solvers for the Discrete -Optimal Transport Problems
M Scetbon
arXiv preprint arXiv:2304.13467, 2023
2023
Advances in Optimal Transport: Low-Rank Structures and Applications in Machine Learning
M Scetbon
Institut Polytechnique de Paris, 2023
2023
A Fixed-Point Approach for Causal Generative Modeling
M Scetbon, J Jennings, A Hilmkil, C Zhang, C Ma
Forty-first International Conference on Machine Learning, 0
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