Publications

Deep learning for AI
Yoshua Bengio
Yann LeCun
Geoffrey Hinton
How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding la… (voir plus)nguage?
2021-06-21
Communications of the ACM (publié)
doi.org
Deep learning for AI
Yoshua Bengio
Yann LeCun
Geoffrey Hinton
2021-06-21
Communications of the ACM (publié)
doi.org
Deep learning for AI
Yoshua Bengio
Yann LeCun
Geoffrey Hinton
2021-06-21
Communications of the ACM (publié)
doi.org
Deep learning for AI
Yoshua Bengio
Yann LeCun
Geoffrey Hinton
2021-06-21
Communications of the ACM (publié)
doi.org
Large-Scale Intrinsic Functional Brain Organization Emerges from Three Canonical Spatiotemporal Patterns
Taylor Bolt
Jason S. Nomi
Danilo Bzdok
Catie Chang
B.T. Yeo
Lucina Q. Uddin
Shella Keilholz
2021-06-20
(publié)
doi.org
A parsimonious description of global functional brain organization in three spatiotemporal patterns
Taylor Bolt
Jason S. Nomi
Danilo Bzdok
Jorge A. Salas
Catie Chang
B. T. Thomas Yeo
Lucina Q. Uddin
S. Keilholz
2021-06-20
Nature Neuroscience (published)
doi.org
A Data Mining Analysis of Cross-Regional Study of Apparel Consumption
Osmud Rahman
Benjamin Fung
2021-06-19
(published)
doi.org
Smart about medications (SAM): a digital solution to enhance medication management following hospital discharge
Santiago Márquez Fosser
Nadar Mahmoud
Bettina Habib
Daniala L Weir
Fiona Chan
Rola El Halabieh
Jeanne Vachon
Manish Thakur
Thai Tran
Melissa Bustillo
Caroline Beauchamp
André Bonnici
David Buckeridge
Robyn Tamblyn
2021-06-18
JAMIA Open (publié)
doi.org
The Cost of Untracked Diversity in Brain-Imaging Prediction
Oualid Benkarim
Casey Paquola
Bo-yong Park
Valeria Kebets
Seok-Jun Hong
Reinder Vos de Wael
Shaoshi Zhang
B.T. Thomas Yeo
Michael Eickenberg
Tian Ge
Jean-Baptiste Poline
Boris C Bernhardt
Danilo Bzdok
2021-06-17
bioRxiv (prépublication)
doi.org
SPeCiaL: Self-Supervised Pretraining for Continual Learning
Lucas Caccia
Joelle Pineau
2021-06-16
ArXiv (preprint)
doi.org
arxiv.org
Improving Continuous Normalizing Flows using a Multi-Resolution Framework
Vikram Voleti
Chris Finlay
Adam M. Oberman
Chris Pal
Recent work has shown that Continuous Normalizing Flows (CNFs) can serve as generative models of images with exact likelihood calculation an… (voir plus)d invertible generation/density estimation. In this work we introduce a Multi-Resolution variant of such models (MRCNF). We introduce a transformation between resolutions that allows for no change in the log likelihood. We show that this approach yields comparable likelihood values for various image datasets, with improved performance at higher resolutions, with fewer parameters, using only 1 GPU.
2021-06-15
ICML.cc/2021/Workshop/INNF (poster)
openreview.net
openreview.net
Randomized Exploration for Reinforcement Learning with General Value Function Approximation
Haque Ishfaq
Qiwen Cui
Viet Huy Nguyen
Alex Ayoub
Zhuoran Yang
Zhaoran Wang
Doina Precup
Lin F. Yang
We propose a model-free reinforcement learning algorithm inspired by the popular randomized least squares value iteration (RLSVI) algorithm … (voir plus)as well as the optimism principle. Unlike existing upper-confidence-bound (UCB) based approaches, which are often computationally intractable, our algorithm drives exploration by simply perturbing the training data with judiciously chosen i.i.d. scalar noises. To attain optimistic value function estimation without resorting to a UCB-style bonus, we introduce an optimistic reward sampling procedure. When the value functions can be represented by a function class
2021-06-15
ArXiv (prépublication)
arxiv.org
arxiv.org