Symplectic encoders for physics-constrained variational dynamics inference

We propose a new variational autoencoder (VAE) with physical constraints capable of learning the dynamics of Multiple Degree of Freedom (MDOF) dynamic systems. Standard variational autoencoders place greater emphasis on compression than interpretability regarding the learned latent space. We propose...

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Detalles Bibliográficos
Autores principales: Bacsa, Kiran, Lai, Zhilu, Liu, Wei, Todd, Michael, Chatzi, Eleni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929450/
https://www.ncbi.nlm.nih.gov/pubmed/36788325
http://dx.doi.org/10.1038/s41598-023-29186-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929450/
https://www.ncbi.nlm.nih.gov/pubmed/36788325
http://dx.doi.org/10.1038/s41598-023-29186-8

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