Physics-integrated generative modeling using attentive planar normalizing flow based variational autoencoder

arXiv:2404.12267v1 Announce Type: new
Abstract: Physics-integrated generative modeling is a class of hybrid or grey-box modeling in which we augment the the data-driven model with the physics knowledge governing the data distribution. The use of physics knowledge allows the generative model to produce output in a controlled way, so that the output, by construction, complies with the physical laws. It imparts improved generalization ability to extrapolate beyond the training distribution as well as improved interpretability because the model is partly …

abstract arxiv autoencoder box class cs.ai cs.lg data data-driven distribution flow generative generative modeling hybrid knowledge modeling physics stat.ml type