Workshop on Mean Field Games, Optimal Transport and Machine Learning

This workshop aims to bring closer researchers at the intersection of mean field games, optimal transport and machine learning

• Jean-David Benamou (Inria Paris)

• Charles Bertucci (École polytechnique)

• Mathieu Blondel (Google DeepMind)

• Joan Bruna (New York University)

• Guillaume Carlier (Université Paris Dauphine)

• Sinho Chewi (Yale University)

• Lénaïc Chizat (EPFL)

• Rama Cont (University of Oxford)

• Arnaud Doucet (Google DeepMind)

• Annette Dumas (Université Paris Dauphine)

• Borjan Geshkovski (Inria Paris)

• Mengjian Hua (NYU Shanghai)

• Matt Jacobs (University of California, Santa Barbara)

• Ziad Kobeissi (Inria Saclay)

• Shuyang Ling (NYU Shanghai)

• Sibylle Marcotte (ENS Paris)

• Quentin Mérigot (Université Paris-Saclay)

• Alpár R. Mészáros (Durham University)

• Gabriel Peyré (ENS Paris)

• Huyên Pham (Ecole Polytechnique)

• Zhenjie Ren (Université Évry Paris-Saclay)

• Maxime Sylvestre (Université Paris Dauphine)

• Esteban G. Tabak (New York University)

• Nizar Touzi (New York University)

• Eric Vanden-Eijnden (New York University)

• Renyuan Xu (New York University)

• Jiayang Yin (NYU Shanghai)

Mathieu Laurière (NYU Shanghai) Flavien Léger (Inria Paris)

This workshop is sponsored in part by an NYU Global Opportunity Grant and by Inria Paris, and supported by NYU Paris.