Graph Learning in Physical-informed Mesh-reduced Space for Real-world Dynamic Systems

Author:

Hu Yeping1ORCID,Lei Bo1ORCID,Castillo Victor M.1ORCID

Affiliation:

1. Lawrence Livermore National Laboratory, Livermore, CA, USA

Publisher

ACM

Reference45 articles.

1. Flow-based generative models for Markov chain Monte Carlo in lattice field theory

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3. Uri Alon and Eran Yahav . 2020. On the bottleneck of graph neural networks and its practical implications. arXiv preprint arXiv:2006.05205 ( 2020 ). Uri Alon and Eran Yahav. 2020. On the bottleneck of graph neural networks and its practical implications. arXiv preprint arXiv:2006.05205 (2020).

4. Subgraph neural networks;Alsentzer Emily;Advances in Neural Information Processing Systems,2020

5. Peter W Battaglia Jessica B Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vinicius Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner etal 2018. Relational inductive biases deep learning and graph networks. arXiv preprint arXiv:1806.01261 (2018). Peter W Battaglia Jessica B Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vinicius Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner et al. 2018. Relational inductive biases deep learning and graph networks. arXiv preprint arXiv:1806.01261 (2018).

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