Modeling Spatio-Temporal Dynamical Systems With Neural Discrete Learning and Levels-of-Experts-Reference-Cited by-同舟云学术

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Modeling Spatio-Temporal Dynamical Systems With Neural Discrete Learning and Levels-of-Experts

Published:2024-08 Issue:8 Volume:36 Page:4050-4062
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Wang Kun¹^ORCID,Wu Hao¹^ORCID,Zhang Guibin²^ORCID,Fang Junfeng¹^ORCID,Liang Yuxuan³^ORCID,Wu Yuankai⁴^ORCID,Zimmermann Roger⁵^ORCID,Wang Yang¹^ORCID

Affiliation:

1. University of Science and Technology of China, Hefei, Anhui, China

2. Tongji University, Shanghai, China

3. INTR Thrust & DSA Thrust, The Hong Kong University of Science and Technology, Guangzhou, Guangdong, China

4. College of Computer Science, Sichuan University, Chengdu, Sichuan, China

5. University of Singapore, Singapore

Funder

National Natural Science Foundation of China

Youth Team in Basic Research Field, CAS

Academic Leaders Cultivation Program

University of Science and Technology of China

Guangzhou-HKUST(GZ) Joint Funding Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/69/10589999/10428110.pdf?arnumber=10428110

Reference125 articles.

1. Mathematical Truth

2. Physical Symbol Systems*

3. Multiphysics Modeling Using COMSOL®4

4. The Principles of Deep Learning Theory

5. Deep-Learning Approach to First-Principles Transport Simulations

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