Rethinking Controllable Variational Autoencoders-Reference-Cited by-同舟云学术

Rethinking Controllable Variational Autoencoders

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Shao Huajie¹,Yang Yifei²,Lin Haohong³,Lin Longzhong²,Chen Yizhuo²,Yang Qinmin²,Zhao Han⁴

Affiliation:

1. College of Willam and Mary

2. Zhejiang University

3. Carnegie Mellon University

4. University of Illinois at Urbana-Champaign

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09879937.pdf?arnumber=9879937

Reference49 articles.

1. Controlvae: Tuning, analytical properties, and performance analysis;shao;Arxiv preprint arXiv,2020

2. The setpoint overshoot method: A simple and fast closed-loop approach for PID tuning

3. Variational discriminator bottleneck: Im-proving imitation learning, inverse rl, and gans by constraining information flow;peng;Arxiv preprint arXiv,2018

4. Contrastive disentanglement in generative adversarial networks;pan;Arxiv preprint arXiv,2021

5. A method for auto-tuning of PID control parameters

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