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From the String Landscape to the Mathematical Landscape: A Machine-Learning Outlook

He, Y-H. ORCID: 0000-0002-0787-8380 (2023). From the String Landscape to the Mathematical Landscape: A Machine-Learning Outlook. In: Lie Theory and Its Applications in Physics. International Workshop on Lie Theory and Its Applications in Physics, 20-26 Jun 2021, Sofia, Bulgaria. doi: 10.1007/978-981-19-4751-3_2


We review the recent programme of using machine-learning to explore the landscape of mathematical problems. With this paradigm as a model for human intuition—complementary to and in contrast with the more formalistic approach of automated theorem proving—we highlight some experiments on how AI helps with conjecture formulation, pattern recognition and computation.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: his version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: 10.1007/978-981-19-4751-3_2
Subjects: Q Science > QA Mathematics
Departments: School of Science & Technology
School of Science & Technology > Mathematics
SWORD Depositor:
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