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Improving unsupervised anomaly localization by applying multi-scale memories to autoencoders

Dec 21, 2020
Yifei Yang, Shibing Xiang, Ruixiang Zhang


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Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective

Jul 21, 2020
Ruixiang Zhang, Masanori Koyama, katsuhiko Ishiguro

* ICML2020 accepted paper 

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Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling

Mar 24, 2020
Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio


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Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models

Nov 18, 2019
Tong Che, Xiaofeng Liu, Site Li, Yubin Ge, Ruixiang Zhang, Caiming Xiong, Yoshua Bengio


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Perceptual Generative Autoencoders

Jun 25, 2019
Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull


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Understanding Hidden Memories of Recurrent Neural Networks

Oct 30, 2017
Yao Ming, Shaozu Cao, Ruixiang Zhang, Zhen Li, Yuanzhe Chen, Yangqiu Song, Huamin Qu

* Published at IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017) 

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Maximum-Likelihood Augmented Discrete Generative Adversarial Networks

Feb 26, 2017
Tong Che, Yanran Li, Ruixiang Zhang, R Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio

* 11 pages, 3 figures 

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