Multimodal Learning for Materials

arXiv:2312.00111v2 Announce Type: replace
Abstract: Artificial intelligence is transforming computational materials science, improving the prediction of material properties, and accelerating the discovery of novel materials. Recently, publicly available material data repositories have grown rapidly. This growth encompasses not only more materials, but also a greater variety and quantity of their associated properties. Existing machine learning efforts in materials science focus primarily on single-modality tasks, i.e., relationships between materials and a single physical property, thus not taking advantage of the rich …

abstract artificial artificial intelligence arxiv computational cond-mat.mtrl-sci cs.lg data discovery growth improving intelligence machine machine learning material materials materials science multimodal multimodal learning novel prediction repositories science type