Web: http://arxiv.org/abs/2201.11976

Jan. 31, 2022, 2:11 a.m. | Ce Yang, Weihao Gao, Di Wu, Chong Wang

cs.LG updates on arXiv.org arxiv.org

Simulation of the dynamics of physical systems is essential to the
development of both science and engineering. Recently there is an increasing
interest in learning to simulate the dynamics of physical systems using neural
networks. However, existing approaches fail to generalize to physical
substances not in the training set, such as liquids with different viscosities
or elastomers with different elasticities. Here we present a machine learning
method embedded with physical priors and material parameters, which we term as
"Graph-based Physics …

arxiv graph graph neural networks learning networks neural neural networks systems

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