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