Microstructure-based Variational Neural Networks for Robust Uncertainty Quantification in Materials Digital Twins

This article presents a research paper on using variational neural networks for uncertainty quantification in materials science. The focus is on developing more robust methods for digital twins, which are virtual representations of physical objects. The title suggests a technical approach involving microstructure analysis and variational methods.