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.
Interests
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
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