R. Devon Hjelm

Affiliations:
  • Microsoft Research Montreal, Canada
  • Mila - Quebec AI Institute, Montreal, QC, Canada


According to our database1, R. Devon Hjelm authored at least 62 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links.
NeuroImage, January, 2024

On the Modeling Capabilities of Large Language Models for Sequential Decision Making.
CoRR, 2024

Grounding Multimodal Large Language Models in Actions.
CoRR, 2024

Large Language Models as Generalizable Policies for Embodied Tasks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Poly-View Contrastive Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Large Language Models as Generalizable Policies for Embodied Tasks.
CoRR, 2023

Value function estimation using conditional diffusion models for control.
CoRR, 2023

2022
PatchBlender: A Motion Prior for Video Transformers.
CoRR, 2022

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes.
CoRR, 2022

The Sandbox Environment for Generalizable Agent Research (SEGAR).
CoRR, 2022

Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Robust Contrastive Learning against Noisy Views.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Test Sample Accuracy Scales with Training Sample Density in Neural Networks.
Proceedings of the Conference on Lifelong Learning Agents, 2022

2021
Predicting Unreliable Predictions by Shattering a Neural Network.
CoRR, 2021

Pretraining Representations for Data-Efficient Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding by Understanding Not: Modeling Negation in Language Models.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Data-Efficient Reinforcement Learning with Self-Predictive Representations.
Proceedings of the 9th International Conference on Learning Representations, 2021

CMIM: Cross-Modal Information Maximization For Medical Imaging.
Proceedings of the IEEE International Conference on Acoustics, 2021

Implicit Regularization via Neural Feature Alignment.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Object-Centric Image Generation from Layouts.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations.
CoRR, 2020

Cross-Modal Information Maximization for Medical Imaging: CMIM.
CoRR, 2020

Implicit Regularization in Deep Learning: A View from Function Space.
CoRR, 2020

Representation Learning with Video Deep InfoMax.
CoRR, 2020

Data-Efficient Reinforcement Learning with Momentum Predictive Representations.
CoRR, 2020

Deep Reinforcement and InfoMax Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

An end-to-end approach for the verification problem: learning the right distance.
Proceedings of the 37th International Conference on Machine Learning, 2020

Locality and Compositionality in Zero-Shot Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning.
CoRR, 2019

Spatio-Temporal Deep Graph Infomax.
CoRR, 2019

On Adversarial Mixup Resynthesis.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Representations by Maximizing Mutual Information Across Views.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Unsupervised State Representation Learning in Atari.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Deep Graph Infomax.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning deep representations by mutual information estimation and maximization.
Proceedings of the 7th International Conference on Learning Representations, 2019

Adversarial Mixup Resynthesizers.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Batch Weight for Domain Adaptation With Mass Shift.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Leveraging exploration in off-policy algorithms via normalizing flows.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Prediction of Progression to Alzheimer's disease with Deep InfoMax.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

On-Line Adaptative Curriculum Learning for GANs.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
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, 2018

Keep Drawing It: Iterative language-based image generation and editing.
CoRR, 2018

Learning deep representations by mutual information estimation and maximization.
CoRR, 2018

Online Adaptative Curriculum Learning for GANs.
CoRR, 2018

MINE: Mutual Information Neural Estimation.
CoRR, 2018

Mutual Information Neural Estimation.
Proceedings of the 35th International Conference on Machine Learning, 2018

Boundary Seeking GANs.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
ACtuAL: Actor-Critic Under Adversarial Learning.
CoRR, 2017

Boundary-Seeking Generative Adversarial Networks.
CoRR, 2017

Maximum-Likelihood Augmented Discrete Generative Adversarial Networks.
CoRR, 2017

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A deep-learning approach to translate between brain structure and functional connectivity.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data.
CoRR, 2016

Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data.
CoRR, 2016

Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach.
Proceedings of the 2016 IEEE Southwest Symposium on Image Analysis and Interpretation, 2016

Iterative Refinement of the Approximate Posterior for Directed Belief Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia.
NeuroImage, 2015

Iterative Refinement of Approximate Posterior for Training Directed Belief Networks.
CoRR, 2015

Deep independence network analysis of structural brain imaging: A simulation study.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

2014
Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks.
NeuroImage, 2014

Deep learning for neuroimaging: a validation study.
Proceedings of the 2nd International Conference on Learning Representations, 2014


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