Yann Ollivier

Paris, France

After receiving a Ph.D. in probability and group theory, Yann joined the CNRS, the French national research institute. He initially worked on unveiling connections between probability, Markov chains, differential geometry, and discrete geometry. For this work, he was awarded the bronze medal of the CNRS. Due to a lifelong interest in artificial intelligence, Yann focused his research on machine learning and joined the computer science department at Paris-Sud University. Following the industrial development of deep learning, he joined Facebook AI Research. Yann works on understanding and improving the learning algorithms for neural networks. In the long term, he is interested in building general artificial intelligence systems. More specific fields of interest include the geometry of gradient descent algorithms, the dynamics of recurrent networks and online learning, better algorithms for reinforcement learning, and what "learning" means in terms of information theory.

Yann's Publications



Separating value functions across time-scales

Joshua Romoff, Peter Henderson, Ahmed Touati, Emma Brunskill, Joelle Pineau, Yann Ollivier,



Making Deep Q-learning Methods Robust to Time Discretization

Corentin Tallec, Léonard Blier, Yann Ollivier,



First-order Adversarial Vulnerability of Neural Networks and Input Dimension

Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Scholkopf, Leon Bottou, David Lopez-Paz,