Deep Neural Networks For Surrogate Modeling And Uncertainty Quantification

Xihaier Luo Ph.D. Candidate What to Expect Developing reliable and robust surrogate models for uncertainty quantification and propagation is a key problem in many scientific and engineering applications, such as structural health monitoring, natural hazard modeling, and environmental process understanding, to name but a few. In this talk, we address two problems regarding surrogate modeling.…
Read More