A VRNN-DIRT framework with tensor trains delivers low-variance failure probability estimates for 3D heterogeneous composites in dimensions up to 150.
Deep importance sampling using tensor trains with application to a priori and a posteriori rare events.SIAM Journal on Scientific Computing, 46(1):C1–C29, 2024
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Multiscale Structural Reliability Analysis in high dimensions with Tensor Trains and Physics-Augmented Neural Networks
A VRNN-DIRT framework with tensor trains delivers low-variance failure probability estimates for 3D heterogeneous composites in dimensions up to 150.