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- W4385618389 abstract "We survey some recent applications of machine learning to problems in geometry and theoretical physics. Pure mathematical data has been compiled over the last few decades by the community, and experiments in supervised, semi-supervised, and unsupervised machine learning have found surprising success. We thus advocate the program of machine learning mathematical structures and formulating conjectures via pattern recognition, in other words using artificial intelligence to help one do mathematics." @default.
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- W4385618389 date "2023-01-01" @default.
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- W4385618389 title "Machine learning in physics and geometry" @default.
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- W4385618389 doi "https://doi.org/10.1016/bs.host.2023.06.002" @default.
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