LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields

LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields

Linear reduced-order modeling (ROM) simplifies complex simulations by approximating the behavior of a system using a simplified kinematic representation. Typically, ROM is trained on input simulations created with a specific spatial discretization, and then serves to accelerate simulations with the...

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Bibliographic Details
Main Authors: Chang, Yue, Chen, Peter Yichen, Wang, Zhecheng, Chiaramonte, Maurizio M., Carlberg, Kevin, Grinspun, Eitan
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: ACM|SIGGRAPH Asia 2023 Conference Papers 2024
Online Access:https://hdl.handle.net/1721.1/153261

Internet

https://hdl.handle.net/1721.1/153261

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