2born (2born) wrote,
2born
2born

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AI Feynman: a Physics-Inspired Method for Symbolic Regression: https://arxiv.org/abs/1905.11481

A core challenge for both physics and artificial intellicence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle, functions of practical interest often exhibit symmetries, separability, compositionality and other simplifying properties. In this spirit, we develop a recursive multidimensional symbolic regression algorithm that combines neural network fitting with a suite of physics-inspired techniques. We apply it to 100 equations from the Feynman Lectures on Physics, and it discovers all of them, while previous publicly available software cracks only 71; for a more difficult test set, we improve the state of the art success rate from 15% to 90%.

14 pages, 2 figs. Our Feynman Symbolic Regression Database for benchmarking can be downloaded at this https URL
Tags: разгребая arXiv'ы, техника
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