Predictive Uncertainty for Neural CAE Surrogates
ScientificML
Investigates how uncertainty quantification approaches perform when adapted to geometry-conditioned neural surrogates for CAE, comparing closed-form and sampling-based methods across varying geometries and engineering quantities of interest.
See LICENSE file neural surrogatesuncertainty quantificationCAE simulation