R. Devon Hjelm

According to our database1, R. Devon Hjelm authored at least 15 papers between 2014 and 2019.

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

Timeline

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Bibliography

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

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

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
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
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

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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