Mila > Team > Devon Hjelm

Devon Hjelm

Affiliate Member
Researcher

I am a deep learning Researcher at Microsoft Research, Montreal. I received my PhD at the University of New Mexico, where I studied learning representations of the brain using graphical models. I did a postdoc under Yoshua Bengio doing unsupervised learning, representation learning, and adversarial models. At Microsoft, I study how to learn better representations for scientific analysis and downstream tasks in RL and NLP.

Publications

2021-12

Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman and Aaron C. Courville
Test Sample Accuracy Scales with Training Sample Density in Neural Networks.
Xu Ji, Razvan Pascanu, Devon Hjelm, Balaji Lakshminarayanan and Andrea Vedaldi
arXiv: Learning
(2021-12-02)
arxiv.orgPDF

2021-06

Predicting Unreliable Predictions by Shattering a Neural Network
Xu Ji, Razvan Pascanu, R. Devon Hjelm, Andrea Vedaldi, Balaji Lakshminarayanan and Yoshua Bengio
arXiv preprint arXiv:2106.08365
(2021-06-15)
ui.adsabs.harvard.edu
CMIM: Cross-Modal Information Maximization For Medical Imaging
Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di Jorio, Margaux Luck, Devon Hjelm and Yoshua Bengio
ICASSP 2021
(2021-06-06)
ieeexplore.ieee.org
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL.
Bogdan Mazoure, Ahmed M. Ahmed, Patrick MacAlpine, R. Devon Hjelm and Andrey Kolobov
arXiv preprint arXiv:2106.02193
(2021-06-04)
ui.adsabs.harvard.eduPDF

2021-05

Understanding by Understanding Not: Modeling Negation in Language Models.
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni and Aaron C. Courville
Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville and Philip Bachman

2021-03

Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent and Simon Lacoste-Julien
Pretraining Reward-Free Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman and Aaron Courville
ICLR 2021
(2021-03-09)
openreview.netPDF

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)
ui.adsabs.harvard.eduPDF

2020-08

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.com

2020-07

Data-Efficient Reinforcement Learning with Momentum Predictive Representations. (arXiv:2007.05929v2 [cs.LG] UPDATED)
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville and Philip Bachman
arXiv Computer Science
(2020-07-24)
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

2020-06

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

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

2019-12

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
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

2019-09

Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau and R Devon Hjelm
arXiv: Learning
(2019-09-25)
ui.adsabs.harvard.eduPDF

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

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
Leveraging exploration in off-policy algorithms via normalizing flows
Bogdan Mazoure, Thang Doan, Audrey Durand, R Devon Hjelm and Joelle Pineau
arXiv preprint arXiv:1905.06893
(2019-05-16)
ui.adsabs.harvard.eduPDF

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)
ui.adsabs.harvard.eduPDF

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, Joelle Pineau and R. Devon Hjelm
Conference on Robot Learning
(2019-01-01)
proceedings.mlr.pressPDF
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, Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio and Graham W. Taylor
NEURIPS 2018
(2018-11-24)
[LATEST on None (2018-11-24)]

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

2018-06

Mine: mutual information neural estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, Aaron Courville and Devon Hjelm
ICML 2018
(2018-06-07)
www.microsoft.com

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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