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Is deep learning a useful tool for the pure mathematician?
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A personal and informal account of what a pure mathematician might expect when using tools from deep learning in their research.
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Cited by 3 Pith papers
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Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?
A neural network relaxation of geometric coloring constraints produced new plane colorings, including an almost 5-coloring covering all but 3.74% of the plane, improving known bounds for Hadwiger-Nelson variants.
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A Hybrid Framework for Healing Semigroups with Machine Learning
A hybrid random-forest-plus-deterministic method heals corrupted finite semigroup tables, restoring associativity in 95% of small cases and 60% at n=10.
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Explaining Deep Network Classification of Matrices: A Case Study on Monotonicity
For random 7x7 matrices with entries uniform in (-1,1), the ratio of the two lowest characteristic-polynomial coefficients, equal to 1/tr(A^{-1}) for monotone A, is empirically below 0.1755 for all 18,000 sampled mono...
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