Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models

Govinda Anantha Padmanabha, Jan Niklas Fuhg, Cosmin Safta +2

Most scientific machine learning (SciML) applications of neural networks involve hundreds to thousands of parameters, and hence, uncertainty quantification for such models is plagu…