Foundation Model for Material Science

نویسندگان

چکیده

Foundation models (FMs) are achieving remarkable successes to realize complex downstream tasks in domains including natural language and visions. In this paper, we propose building an FM for material science, which is trained with massive data across a wide variety of modalities. Nowadays machine learning play key roles discovery, particularly property prediction structure generation. However, those have been independently developed address only specific without sharing more global knowledge. Development science will enable overarching modeling modalities by their feature representations. We discuss fundamental challenges required technologies build from the aspects preparation, model development, tasks.

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ژورنال

عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence

سال: 2023

ISSN: ['2159-5399', '2374-3468']

DOI: https://doi.org/10.1609/aaai.v37i13.26793