NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators. (arXiv:2208.11866v1 [cs.LG])

Uncertainty quantification (UQ) in machine learning is currently drawing
increasing research interest, driven by the rapid deployment of deep neural
networks across different fields, such as computer vision, natural language
processing, and the need for reliable tools in risk-sensitive applications.
Recently, various machine learning models have also been developed to tackle
problems in the field of scientific computing with applications to
computational science and engineering (CSE). Physics-informed neural networks
and deep operator networks are two such models for solving partial …

arxiv lg library operators quantification uncertainty