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Evaluating the diversity and utility of materials proposed by generative models
Generative machine learning models can use data generated by scientific modeling to create large quantities of novel material structures.
Curvature-informed multi-task learning for graph networks
Properties of interest for crystals and molecules, such as band gap, elasticity, and solubility, are generally related to each other: they are governed by the same underlying laws of physics.
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