
A semi-supervised disentangled variational autoencoder is developed to efficiently and interpretably design single-phase high-entropy alloys by learning a probabilistic relationship between materials representations and target properties.


coremsg

data-efficient-and-interpretable-inverse-design-of-single-phase-high-entropy-alloys-using-a-disentangled-variational-autoencoder


Data-Efficient and Interpretable Inverse Design of Single-Phase High-Entropy Alloys using a Disentangled Variational Autoencoder
