Pascal Vincent

Research Scientist

I am a Research Scientist at Facebook AI Research (FAIR) in Montreal, as well as an Associate Professor in the Department of Computer Science and Operations Research at Université de Montréal, a founding member of the Montreal Institute for Learning Algorithms (MILA) and Associate Fellow in the Canadian Institute for Advanced Research (CIFAR / Learning Machines and Brains program).

I have been conducting research on artificial neural networks since 1995 and completed a PhD in computer-science/machine-learning at Université de Montréal under the direction of Yoshua Bengio in 2004. My primary research focus is the development of original approaches for representation learning that aim to be both statistically and computationally efficient, in order to enable the learning of more meaningful and practically useful representations across multiple application domains such as vision and language understanding.


AI, machine learning, image and language understanding, and optimization.

Latest Publications

NeurIPS - December 7, 2020

Adversarial Example Games

Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton

UAI - August 4, 2020

Stable Policy Optimization via Off-Policy Divergence Regularization

Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent

ICML - July 12, 2020

Stochastic Hamiltonian Gradient Methods for Smooth Games

Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

ICLR - April 20, 2020

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks

Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien

UAI - June 21, 2019

Randomized Value Functions via Multiplicative Normalizing Flows

Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent

CVPR - June 16, 2019

Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition

Zizhao Zhang, Adriana Romero, Matthew J. Muckley, Pascal Vincent, Lin Yang, Michal Drozdzal

ICML - June 10, 2019

Unreproducible Research is Reproducible

Xavier Bouthillier, Cesar Laurent, Pascal Vincent

ICLR - May 6, 2019

A Variational Inequality Perspective on Generative Adversarial Networks

Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

NeurIPS 2018 - December 6, 2018

Fast Approximate Natural Gradient Descent in a Kronecker-factored Eigenbasis

Thomas George, Cesar Laurent, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent

EMNLP 2018 - October 31, 2018

Auto-Encoding Dictionary Definitions into Consistent Word Embeddings

Tom Bosc, Pascal Vincent

ICML 2018 - July 11, 2018

Convergent TREE BACKUP and RETRACE with Function Approximation

Ahmed Touati, Pierre-Luc Bacon, Doina Precup, Pascal Vincent

CVPR 2018 - June 18, 2018

Improving Landmark Localization with Semi-Supervised Learning

Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher Pal, Jan Kautz

ICLR 2018 - April 30, 2018

An Evaluation of Fisher Approximations Beyond Kronecker Factorization

Cesar Laurent, Thomas George, Xavier Bouthillier, Nicolas Ballas, Pascal Vincent

ICLR 2018 - April 30, 2018

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling

Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien

arXiv - March 14, 2018

Learning to Compute Word Embeddings On the Fly

Dzmitry Bahdanau, Tom Bosc, Stanislaw Jastrzebski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio