Abstract
Over the recent years deep learning has found successful applications in mathematical reasoning. Today, we can predict fine-grained proof steps, relevant premises, and even useful conjectures using neural networks. This extended abstract summarizes recent developments of machine learning in mathematical reasoning and the vision of the N2Formal group at Google Research to create an automatic mathematician. The second part discusses the key challenges on the road ahead.
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CITATION STYLE
Rabe, M. N., & Szegedy, C. (2021). Towards the Automatic Mathematician. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12699 LNAI, pp. 25–37). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-79876-5_2
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