Recent Advances for Quantum Neural Networks in Generative Learning-Reference-Cited by-同舟云学术

Recent Advances for Quantum Neural Networks in Generative Learning

Published:2023 Issue: Volume: Page:1-20
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Tian Jinkai¹,Sun Xiaoyu²,Du Yuxuan³^ORCID,Zhao Shanshan³^ORCID,Liu Qing⁴,Zhang Kaining⁵,Yi Wei¹,Huang Wanrong¹,Wang Chaoyue³^ORCID,Wu Xingyao³,Hsieh Min-Hsiu⁶^ORCID,Liu Tongliang⁵^ORCID,Yang Wenjing⁷,Tao Dacheng³^ORCID

Affiliation:

1. Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China

2. Laboratoire d'Informatique & Systèmes (LIS) UMR 7020, Aix-Marseille University, Marseille, France

3. JD Explore Academy, Beijing, China

4. School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore

5. University of Sydney, Darlington, NSW, Australia

6. Hon Hai (Foxconn) Research Institute, Taipei, Taiwai

7. Institute for Quantum Information & State Key Laboratory of High Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/4359286/10113742.pdf?arnumber=10113742

Reference238 articles.

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2. Enhancing Generative Models via Quantum Correlations

3. A tutorial on energy-based learning;lecun;Predicting Structured Data,2006

4. Theory of quantum generative learning models with maximum mean discrepancy;du,2022

5. Auto-encoding variational bayes;kingma;Proc 2nd Int Conf Learn Representations,2014

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