Neural Symbolic Regression that scales (2021)

https://proceedings.mlr.press/v139/biggio21a.html

by liamdgray • 11 months ago

1 1 11 months ago

proceedings.mlr.press

liamdgray• 11 months ago

Abstract: "Symbolic equations are at the core of scientific discovery. The task of discovering the underlying equation from a set of input-output pairs is called symbolic regression. Traditionally, symbolic regression methods use hand-designed strategies that do not improve with experience. In this paper, we introduce the first symbolic regression method that leverages large scale pre-training. We procedurally generate an unbounded set of equations, and simultaneously pre-train a Transformer to predict the symbolic equation from a corresponding set of input-output-pairs. At test time, we query the model on a new set of points and use its output to guide the search for the equation. We show empirically that this approach can re-discover a set of well-known physical equations, and that it improves over time with more data and compute."

Neural Symbolic Regression that scales (2021)

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