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ORCIDR. Devon Hjelm
Person information
- affiliation: Microsoft Research Montreal, Canada
- affiliation: Mila - Quebec AI Institute, Montreal, QC, Canada
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2020 – today
- 2024
[j4]Alex Fedorov
, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, Girish Mittapalle, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun:
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 285: 120485 (2024)- [c33]Amitis Shidani, R. Devon Hjelm, Jason Ramapuram, Russell Webb, Eeshan Gunesh Dhekane, Dan Busbridge:
Poly-View Contrastive Learning. ICLR 2024 - [c32]Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Rin Metcalf, Walter Talbott, Natalie Mackraz, R. Devon Hjelm, Alexander T. Toshev:
Large Language Models as Generalizable Policies for Embodied Tasks. ICLR 2024 - [i42]Amitis Shidani, R. Devon Hjelm, Jason Ramapuram, Russ Webb, Eeshan Gunesh Dhekane, Dan Busbridge:
Poly-View Contrastive Learning. CoRR abs/2403.05490 (2024) - [i41]Andrew Szot, Bogdan Mazoure, Harsh Agrawal, R. Devon Hjelm, Zsolt Kira, Alexander Toshev:
Grounding Multimodal Large Language Models in Actions. CoRR abs/2406.07904 (2024) - [i40]Martin Klissarov, R. Devon Hjelm, Alexander Toshev, Bogdan Mazoure:
On the Modeling Capabilities of Large Language Models for Sequential Decision Making. CoRR abs/2410.05656 (2024) - 2023
- [i39]Bogdan Mazoure, Walter Talbott, Miguel Ángel Bautista, R. Devon Hjelm, Alexander Toshev, Joshua M. Susskind:
Value function estimation using conditional diffusion models for control. CoRR abs/2306.07290 (2023) - [i38]Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Walter Talbott, Katherine Metcalf, Natalie Mackraz, R. Devon Hjelm, Alexander Toshev:
Large Language Models as Generalizable Policies for Embodied Tasks. CoRR abs/2310.17722 (2023) - 2022
- [c31]Xu Ji, Razvan Pascanu, R. Devon Hjelm, Balaji Lakshminarayanan, Andrea Vedaldi:
Test Sample Accuracy Scales with Training Sample Density in Neural Networks. CoLLAs 2022: 629-646 - [c30]Ching-Yao Chuang, R. Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song:
Robust Contrastive Learning against Noisy Views. CVPR 2022: 16649-16660 - [c29]Bogdan Mazoure, Ahmed M. Ahmed, R. Devon Hjelm, Andrey Kolobov, Patrick MacAlpine:
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. ICLR 2022 - [i37]Ching-Yao Chuang, R. Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song:
Robust Contrastive Learning against Noisy Views. CoRR abs/2201.04309 (2022) - [i36]R. Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Frujeri, Mihai Jalobeanu, Andrey Kolobov:
The Sandbox Environment for Generalizable Agent Research (SEGAR). CoRR abs/2203.10351 (2022) - [i35]Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun:
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. CoRR abs/2209.02876 (2022) - [i34]Gabriele Prato, Yale Song, Janarthanan Rajendran, R. Devon Hjelm, Neel Joshi, Sarath Chandar:
PatchBlender: A Motion Prior for Video Transformers. CoRR abs/2211.14449 (2022) - 2021
- [c28]Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma:
Object-Centric Image Generation from Layouts. AAAI 2021: 2647-2655 - [c27]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization via Neural Feature Alignment. AISTATS 2021: 2269-2277 - [c26]Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio:
CMIM: Cross-Modal Information Maximization For Medical Imaging. ICASSP 2021: 1190-1194 - [c25]Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR 2021 - [c24]Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni, Aaron C. Courville:
Understanding by Understanding Not: Modeling Negation in Language Models. NAACL-HLT 2021: 1301-1312 - [c23]Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville:
Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS 2021: 12686-12699 - [i33]Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, R. Devon Hjelm, Alessandro Sordoni, Aaron C. Courville:
Understanding by Understanding Not: Modeling Negation in Language Models. CoRR abs/2105.03519 (2021) - [i32]Bogdan Mazoure, Ahmed M. Ahmed, Patrick MacAlpine, R. Devon Hjelm, Andrey Kolobov:
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. CoRR abs/2106.02193 (2021) - [i31]Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville:
Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR abs/2106.04799 (2021) - [i30]Xu Ji, Razvan Pascanu, R. Devon Hjelm, Andrea Vedaldi, Balaji Lakshminarayanan, Yoshua Bengio:
Predicting Unreliable Predictions by Shattering a Neural Network. CoRR abs/2106.08365 (2021) - 2020
- [c22]Tristan Sylvain, Linda Petrini, R. Devon Hjelm:
Locality and Compositionality in Zero-Shot Learning. ICLR 2020 - [c21]João Monteiro, Isabela Albuquerque, Jahangir Alam, R. Devon Hjelm, Tiago H. Falk:
An end-to-end approach for the verification problem: learning the right distance. ICML 2020: 7022-7033 - [c20]Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm:
Deep Reinforcement and InfoMax Learning. NeurIPS 2020 - [i29]João Monteiro, Isabela Albuquerque, Jahangir Alam, R. Devon Hjelm, Tiago H. Falk:
An end-to-end approach for the verification problem: learning the right distance. CoRR abs/2002.09469 (2020) - [i28]Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma:
Object-Centric Image Generation from Layouts. CoRR abs/2003.07449 (2020) - [i27]Bogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm:
Deep Reinforcement and InfoMax Learning. CoRR abs/2006.07217 (2020) - [i26]Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR abs/2007.05929 (2020) - [i25]R. Devon Hjelm, Philip Bachman:
Representation Learning with Video Deep InfoMax. CoRR abs/2007.13278 (2020) - [i24]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization in Deep Learning: A View from Function Space. CoRR abs/2008.00938 (2020) - [i23]Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio:
Cross-Modal Information Maximization for Medical Imaging: CMIM. CoRR abs/2010.10593 (2020) - [i22]Tristan Sylvain, Linda Petrini, R. Devon Hjelm:
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations. CoRR abs/2010.13320 (2020)
2010 – 2019
- 2019
- [c19]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
On-Line Adaptative Curriculum Learning for GANs. AAAI 2019: 3470-3477 - [c18]Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. BHI 2019: 1-5 - [c17]Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL 2019: 430-444 - [c16]Mikolaj Binkowski, R. Devon Hjelm, Aaron C. Courville:
Batch Weight for Domain Adaptation With Mass Shift. ICCV 2019: 1844-1853 - [c15]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. ICCV 2019: 10303-10311 - [c14]Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal:
Adversarial Mixup Resynthesizers. DGS@ICLR 2019 - [c13]R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio:
Learning deep representations by mutual information estimation and maximization. ICLR 2019 - [c12]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. ICLR (Poster) 2019 - [c11]Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal:
On Adversarial Mixup Resynthesis. NeurIPS 2019: 4348-4359 - [c10]Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm:
Unsupervised State Representation Learning in Atari. NeurIPS 2019: 8766-8779 - [c9]Philip Bachman, R. Devon Hjelm, William Buchwalter:
Learning Representations by Maximizing Mutual Information Across Views. NeurIPS 2019: 15509-15519 - [i21]Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal:
Adversarial Mixup Resynthesizers. CoRR abs/1903.02709 (2019) - [i20]Felix L. Opolka, Aaron Solomon, Catalina Cangea, Petar Velickovic, Pietro Liò, R. Devon Hjelm:
Spatio-Temporal Deep Graph Infomax. CoRR abs/1904.06316 (2019) - [i19]Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. CoRR abs/1904.10931 (2019) - [i18]Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR abs/1905.06893 (2019) - [i17]Mikolaj Binkowski, R. Devon Hjelm, Aaron C. Courville:
Batch weight for domain adaptation with mass shift. CoRR abs/1905.12760 (2019) - [i16]Philip Bachman, R. Devon Hjelm, William Buchwalter:
Learning Representations by Maximizing Mutual Information Across Views. CoRR abs/1906.00910 (2019) - [i15]Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm:
Unsupervised State Representation Learning in Atari. CoRR abs/1906.08226 (2019) - [i14]Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. CoRR abs/1909.07543 (2019) - [i13]Tristan Sylvain, Linda Petrini, R. Devon Hjelm:
Locality and compositionality in zero-shot learning. CoRR abs/1912.12179 (2019) - 2018
- [j3]Sergey M. Plis, Md Faijul Amin, Adam Chekroud, R. Devon Hjelm, Eswar Damaraju, Hyo Jong Lee, Juan R. Bustillo, KyungHyun Cho, Godfrey D. Pearlson, Vince D. Calhoun:
Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia. NeuroImage 181: 734-747 (2018) - [c8]R. Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho, Yoshua Bengio:
Boundary Seeking GANs. ICLR (Poster) 2018 - [c7]Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, R. Devon Hjelm, Aaron C. Courville:
Mutual Information Neural Estimation. ICML 2018: 530-539 - [i12]Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R. Devon Hjelm, Aaron C. Courville:
MINE: Mutual Information Neural Estimation. CoRR abs/1801.04062 (2018) - [i11]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Online Adaptative Curriculum Learning for GANs. CoRR abs/1808.00020 (2018) - [i10]R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Adam Trischler, Yoshua Bengio:
Learning deep representations by mutual information estimation and maximization. CoRR abs/1808.06670 (2018) - [i9]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. CoRR abs/1809.10341 (2018) - [i8]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Keep Drawing It: Iterative language-based image generation and editing. CoRR abs/1811.09845 (2018) - 2017
- [c6]Vince D. Calhoun, Md Faijul Amin, R. Devon Hjelm, Eswar Damaraju, Sergey M. Plis:
A deep-learning approach to translate between brain structure and functional connectivity. ICASSP 2017: 6155-6159 - [c5]Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio:
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. NIPS 2017: 5089-5098 - [i7]Tong Che, Yanran Li, Ruixiang Zhang, R. Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio:
Maximum-Likelihood Augmented Discrete Generative Adversarial Networks. CoRR abs/1702.07983 (2017) - [i6]R. Devon Hjelm, Athul Paul Jacob, Tong Che, Kyunghyun Cho, Yoshua Bengio:
Boundary-Seeking Generative Adversarial Networks. CoRR abs/1702.08431 (2017) - [i5]Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R. Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio:
ACtuAL: Actor-Critic Under Adversarial Learning. CoRR abs/1711.04755 (2017) - [i4]Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio:
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. CoRR abs/1712.04120 (2017) - 2016
- [c4]R. Devon Hjelm, Russ Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince D. Calhoun, Junyoung Chung:
Iterative Refinement of the Approximate Posterior for Directed Belief Networks. NIPS 2016: 4691-4699 - [c3]Md Faijul Amin, Sergey M. Plis, Eswar Damaraju, R. Devon Hjelm, Kyunghyun Cho, Vince D. Calhoun:
Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach. SSIAI 2016: 1-4 - [i3]R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun:
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data. CoRR abs/1603.06624 (2016) - [i2]R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun:
Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data. CoRR abs/1611.00864 (2016) - 2015
- [j2]Qingbao Yu, Erik B. Erhardt, Jing Sui, Yuhui Du, Hao He, R. Devon Hjelm, Mustafa S. Çetin, Srinivas Rachakonda, Robyn L. Miller, Godfrey D. Pearlson, Vince D. Calhoun:
Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia. NeuroImage 107: 345-355 (2015) - [c2]Eduardo Castro, R. Devon Hjelm, Sergey M. Plis, Laurent Dinh, Jessica A. Turner, Vince D. Calhoun:
Deep independence network analysis of structural brain imaging: A simulation study. MLSP 2015: 1-6 - [i1]R. Devon Hjelm, Kyunghyun Cho, Junyoung Chung, Ruslan Salakhutdinov, Vince D. Calhoun, Nebojsa Jojic:
Iterative Refinement of Approximate Posterior for Training Directed Belief Networks. CoRR abs/1511.06382 (2015) - 2014
- [j1]R. Devon Hjelm, Vince D. Calhoun, Ruslan Salakhutdinov, Elena A. Allen, Tülay Adali, Sergey M. Plis:
Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks. NeuroImage 96: 245-260 (2014) - [c1]Sergey M. Plis, R. Devon Hjelm, Ruslan Salakhutdinov, Vince D. Calhoun:
Deep learning for neuroimaging: a validation study. ICLR (Workshop Poster) 2014
Coauthor Index
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