Data-driven spatiotemporal modeling for structural dynamics on irregular domains by stochastic dependency neural estimation

DOI10.1016/j.cma.2022.115831OpenAlexW4311796592MaRDI QIDQ2678544

Yanyan Li

Publication date: 23 January 2023

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2022.115831

zbMATH Keywords

deep learningspatiotemporal dynamicsdata-driven modelinggraph neural networks

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Biology and other natural sciences (92-XX)

Related Items (1)

Resolution-independent generative models based on operator learning for physics-constrained Bayesian inverse problems

Uses Software

• MLMSRBF
• darch

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