Meyer Scetbon

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 33

Top Topics

Linear Regression

Nash Equilibria

Conditional Independence

Top Venues

Publications

Meyer Scetbon, Joel Jennings, Agrin Hilmkil, Cheng Zhang, Chao Ma
FiP: a Fixed-Point Approach for Causal Generative Modeling. CoRR (2024)
Tarun Gupta, Wenbo Gong, Chao Ma, Nick Pawlowski, Agrin Hilmkil, Meyer Scetbon, Ade Famoti, Ashley Juan Llorens, Jianfeng Gao, Stefan Bauer, Danica Kragic, Bernhard Schölkopf, Cheng Zhang
The Essential Role of Causality in Foundation World Models for Embodied AI. CoRR (2024)
Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang
Deep End-to-end Causal Inference. Trans. Mach. Learn. Res. 2024 (2024)
Meyer Scetbon, Elvis Dohmatob
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond. CoRR (2023)
Meyer Scetbon, Elvis Dohmatob
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond. AISTATS (2023)
Meyer Scetbon
Polynomial-Time Solvers for the Discrete ∞-Optimal Transport Problems. CoRR (2023)
Elvis Dohmatob, Meyer Scetbon
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms. CoRR (2023)
Meyer Scetbon, Michal Klein, Giovanni Palla, Marco Cuturi
Unbalanced Low-rank Optimal Transport Solvers. NeurIPS (2023)
Meyer Scetbon, Michal Klein, Giovanni Palla, Marco Cuturi
Unbalanced Low-rank Optimal Transport Solvers. CoRR (2023)
Meyer Scetbon, Gabriel Peyré, Marco Cuturi
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. ICML (2022)
Meyer Scetbon, Laurent Meunier, Yaniv Romano
An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings. ICML (2022)
Meyer Scetbon, Marco Cuturi
Low-rank Optimal Transport: Approximation, Statistics and Debiasing. NeurIPS (2022)
Meyer Scetbon, Marco Cuturi
Low-rank Optimal Transport: Approximation, Statistics and Debiasing. CoRR (2022)
Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. AISTATS (2022)
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Low-Rank Sinkhorn Factorization. ICML (2021)
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Mixed Nash Equilibria in the Adversarial Examples Game. CoRR (2021)
Meyer Scetbon, Gabriel Peyré, Marco Cuturi
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. CoRR (2021)
Meyer Scetbon, Zaïd Harchaoui
A Spectral Analysis of Dot-product Kernels. AISTATS (2021)
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Mixed Nash Equilibria in the Adversarial Examples Game. ICML (2021)
Meyer Scetbon, Michael Elad, Peyman Milanfar
Deep K-SVD Denoising. IEEE Trans. Image Process. 30 (2021)
Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi
Equitable and Optimal Transport with Multiple Agents. AISTATS (2021)
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Low-Rank Sinkhorn Factorization. CoRR (2021)
Meyer Scetbon, Laurent Meunier, Yaniv Romano
-based Kernel Conditional Independence Test. CoRR (2021)
Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. CoRR (2021)
Meyer Scetbon, Marco Cuturi
Linear Time Sinkhorn Divergences using Positive Features. CoRR (2020)
Meyer Scetbon, Zaïd Harchaoui
Harmonic Decompositions of Convolutional Networks. ICML (2020)
Meyer Scetbon, Zaïd Harchaoui
Harmonic Decompositions of Convolutional Networks. CoRR (2020)
Meyer Scetbon, Marco Cuturi
Linear Time Sinkhorn Divergences using Positive Features. NeurIPS (2020)
Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi
Handling Multiple Costs in Optimal Transport: Strong Duality and Efficient Computation. CoRR (2020)
Meyer Scetbon, Zaïd Harchaoui
Risk Bounds for Multi-layer Perceptrons through Spectra of Integral Operators. CoRR (2020)
Meyer Scetbon, Gaël Varoquaux
geometry improves kernel two-sample testing. CoRR (2019)
Meyer Scetbon, Gaël Varoquaux
geometry improves kernel two-sample testing. NeurIPS (2019)
Meyer Scetbon, Michael Elad, Peyman Milanfar
Deep K-SVD Denoising. CoRR (2019)