Devon Hjelm

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Membre Industriel Principal
Devon Hjelm
Professeur associé, Université de Montréal, Microsoft Research
Devon Hjelm

Je suis un chercheur en apprentissage profond à Microsoft Research, à Montréal. J’ai obtenu mon doctorat à l’Université du Nouveau-Mexique, où j’ai étudié l’apprentissage des représentations du cerveau à l’aide de modèles graphiques. J’ai participé à un post-doctorat dirigé par Yoshua Bengio, au sein duquel j’ai réalisé de l’apprentissage non supervisé, de l’apprentissage de représentation puis des modèles accusatoires. Chez Microsoft, j’étudie comment apprendre de meilleures représentations pour des analyses scientifiques et des tâches en aval dans RL et NLP.

 

Publications

2021-05

Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville and Philip Bachman

2020-11

Deep Reinforcement and InfoMax Learning
Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman and R Devon Hjelm

2020-10

Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations.
Tristan Sylvain, Linda Petrini and R. Devon Hjelm
arXiv preprint arXiv:2010.13320
(2020-10-22)
ui.adsabs.harvard.eduPDF
Cross-Modal Information Maximization for Medical Imaging: CMIM.
Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm and Yoshua Bengio
arXiv preprint arXiv:2010.10593
(2020-10-20)
dblp.uni-trier.dePDF

2020-08

Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent and Simon Lacoste-Julien
arXiv: Learning
(2020-08-03)
ui.adsabs.harvard.eduPDF
Implicit Regularization in Deep Learning: A View from Function Space.
Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent and Simon Lacoste-Julien
(venue unknown)
(2020-08-03)
www.microsoft.comPDF

2020-07

Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville and Philip Bachman
ICLR 2020
(2020-07-12)
www.microsoft.comPDF
An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm and Tiago Falk

2020-04

Locality and Compositionality in Zero-Shot Learning
Tristan Sylvain, Linda Petrini and Devon Hjelm

2020-03

Object-Centric Image Generation from Layouts.
Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm and Shikhar Sharma
arXiv preprint arXiv:2003.07449
(2020-03-16)
ui.adsabs.harvard.eduPDF

2019-11

Unsupervised State Representation Learning in Atari
Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté and R Devon Hjelm

2019-10

Batch Weight for Domain Adaptation With Mass Shift
Mikolaj Binkowski, Devon Hjelm and Aaron Courville

2019-09

Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau and R Devon Hjelm
arXiv preprint arXiv:1909.07543
(2019-09-25)
dblp.uni-trier.dePDF

2019-07

On-line Adaptative Curriculum Learning for GANs
Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau and R. Devon Hjelm

2019-06

Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman, R Devon Hjelm and William Buchwalter

2019-05

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio and Graham Taylor
Prediction of Progression to Alzheimer's disease with Deep InfoMax
Alex Fedorov, R Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey Plis and Vince D. Calhoun

2019-04

Spatio-Temporal Deep Graph Infomax.
Felix L. Opolka, Aaron Solomon, Catalina Cangea, Petar Velickovic, Pietro Liò and R. Devon Hjelm
arXiv preprint arXiv:1904.06316
(2019-04-12)
dblp.uni-trier.dePDF

2019-03

Adversarial Mixup Resynthesizers
Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm and Christopher J. Pal

2019-01

Leveraging exploration in off-policy algorithms via normalizing flows.
Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm and Joelle Pineau
On Adversarial Mixup Resynthesis
Christopher Beckham, Sina Honari, Vikas Verma, Alex M. Lamb, Farnoosh Ghadiri, R Devon Hjelm, Yoshua Bengio and Chris Pal

2018-11

Keep Drawing It: Iterative language-based image generation and editing.
Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio and Graham W. Taylor
(venue unknown)
(2018-11-24)
www.microsoft.comPDF

2018-09

Unsupervised one-to-many image translation
Samuel Lavoie-Marchildon, Sebastien Lachapelle, Mikołaj Bińkowski, Aaron Courville, Yoshua Bengio and R Devon Hjelm
(venue unknown)
(2018-09-27)
openreview.netPDF
Deep Graph Infomax
Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio and R. Devon Hjelm

2018-08

Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler and Yoshua Bengio

2018-07

Mutual Information Neural Estimation.
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar, Sherjil Ozair, Yoshua Bengio, Aaron Courville and Devon Hjelm
ICML 2018
(2018-07-03)
proceedings.mlr.pressPDF

2018-02

Learning Generative Models with Locally Disentangled Latent Factors
Brady Neal, Alex Lamb, Sherjil Ozair, Devon Hjelm, Aaron Courville, Yoshua Bengio and Ioannis Mitliagkas
(venue unknown)
(2018-02-15)
openreview.netPDF
Boundary Seeking GANs
R Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho and Yoshua Bengio
ICLR 2018
(2018-02-15)
www.microsoft.comPDF
Variance Regularizing Adversarial Learning
Karan Grewal, R Devon Hjelm and Yoshua Bengio
arXiv preprint arXiv:1707.00309
(2018-02-15)
128.84.21.199PDF

2018-01

MINE: Mutual Information Neural Estimation.
Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R. Devon Hjelm and Aaron C. Courville
arXiv preprint arXiv:1801.04062
(2018-01-12)
ui.adsabs.harvard.eduPDF

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