Deep importance sampling using tensor trains with application to a priori and a posteriori rare event estimation

Tiangang Cui, Sergey Dolgov, Robert Scheichl

We propose a deep importance sampling method that is suitable for estimating rare event probabilities in high-dimensional problems. We approximate the optimal importance distributi…