Devon Hjelm

Mila > About Mila > Team > Devon Hjelm
Core Industry Member
Devon Hjelm
Adjunct Professor, Université de Montréal, Microsoft Research
Devon Hjelm

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

2021-05

Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville and Philip Bachman
ICLR 2021
(2021-05-03)
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)
arxiv.orgPDF
Cross-Modal Information Maximization for Medical Imaging: CMIM
Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di Jorio, Margaux Luck, Devon Hjelm and Yoshua Bengio
arXiv preprint arXiv:2010.10593
(2020-10-20)
arxiv.orgPDF

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)
arxiv.orgPDF
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
arXiv preprint arXiv:2008.00938
(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
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville and Philip Bachman
arXiv preprint arXiv:2007.05929
(2020-07-12)
dblp.uni-trier.dePDF

2020-06

Deep Reinforcement and InfoMax Learning.
Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman and R. Devon Hjelm
arXiv preprint arXiv:2006.07217
(2020-06-12)
dblp.uni-trier.dePDF

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)
dblp.uni-trier.dePDF

2020-01

Deep Reinforcement and InfoMax Learning
Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman and R Devon Hjelm
NEURIPS 2020
(2020-01-01)
papers.nips.ccPDF

2019-12

Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman, R Devon Hjelm and William Buchwalter
On Adversarial Mixup Resynthesis
Christopher Beckham, Sina Honari, Alex Lamb, vikas verma, Farnoosh Ghadiri, R Devon Hjelm, Yoshua Bengio and Chris Pal
NEURIPS 2019
(2019-12-08)
papers.nips.ccPDF
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: Learning
(2019-09-25)
dblp.uni-trier.dePDF

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
Deep Graph Infomax
Petar Veličković, William Fedus, William L Hamilton, Pietro Liò, Yoshua Bengio and R Devon Hjelm
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
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
On Adversarial Mixup Resynthesis
Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R Devon Hjelm, Yoshua Bengio and Christopher Pal
arXiv preprint arXiv:1903.02709
(2019-03-07)
aps.arxiv.org

2019-01

On-line Adaptative Curriculum Learning for GANs
Thang Doan, Joao B Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau and Devon Hjelm
Leveraging exploration in off-policy algorithms via normalizing flows.
Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm and Joelle Pineau

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

2018-07

Mutual Information Neural Estimator
Mohamed Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, R Devon Hjelm and Aaron Courville
ICML 2018
(2018-07-10)
proceedings.mlr.pressPDF

2018-02

MINE: Mutual Information Neural Estimation
Mohamed Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, Devon Hjelm and Aaron Courville
arXiv preprint arXiv:1801.04062
(2018-02-15)
ui.adsabs.harvard.eduPDF
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

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