Bringing Atomistic Deep Learning to Prime TimeDownload PDF

Published: 22 Oct 2021, Last Modified: 05 May 2023NeurIPS-AI4Science PosterReaders: Everyone
Keywords: atomistic deep learning, scaling, high-performance computing, materials science, chemistry, applied machine learning
TL;DR: We identify four barriers preventing the integration of deep learning, high-performance computing, and materials and molecular sciences and outline promising paths forward.
Abstract: Artificial intelligence has not yet revolutionized the design of materials and molecules. In this perspective, we identify four barriers preventing the integration of atomistic deep learning, molecular science, and high-performance computing. We outline focused research efforts to address the opportunities presented by these challenges.
Track: Attention Track
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