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Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling

Oct 19, 2020
Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu

* work in progress 

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Learning Latent Space Energy-Based Prior Model

Jun 15, 2020
Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

* 22 pages, 4 figures 

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Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC

Jun 12, 2020
Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu


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Joint Training of Variational Auto-Encoder and Latent Energy-Based Model

Jun 10, 2020
Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu


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Learning Deep Generative Models with Short Run Inference Dynamics

Dec 14, 2019
Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu


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Flow Contrastive Estimation of Energy-Based Models

Dec 02, 2019
Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu


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Representation Learning: A Statistical Perspective

Nov 26, 2019
Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

* Annual Review of Statistics and Its Application 2020 

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On Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model

May 27, 2019
Erik Nijkamp, Mitch Hill, Song-Chun Zhu, Ying Nian Wu


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A Generative Model for Sampling High-Performance and Diverse Weights for Neural Networks

May 07, 2019
Lior Deutsch, Erik Nijkamp, Yu Yang

* arXiv admin note: substantial text overlap with arXiv:1801.01952 

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On the Anatomy of MCMC-based Maximum Likelihood Learning of Energy-Based Models

Apr 11, 2019
Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu


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Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model

Dec 28, 2018
Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu


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Building a Telescope to Look Into High-Dimensional Image Spaces

Mar 02, 2018
Mitch Hill, Erik Nijkamp, Song-Chun Zhu


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