A VRNN-DIRT framework with tensor trains delivers low-variance failure probability estimates for 3D heterogeneous composites in dimensions up to 150.
Limit state function identification using support vector machines for discontinuous responses and disjoint failure domains.Probabilistic Engineering Mechanics, 23(1):1–11, 2008
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CE 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.