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Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations
April 16, 2024, 4:42 a.m. | Krzysztof Kacprzyk, Mihaela van der Schaar
cs.LG updates on arXiv.org arxiv.org
Abstract: Symbolic regression has excelled in uncovering equations from physics, chemistry, biology, and related disciplines. However, its effectiveness becomes less certain when applied to experimental data lacking inherent closed-form expressions. Empirically derived relationships, such as entire stress-strain curves, may defy concise closed-form representation, compelling us to explore more adaptive modeling approaches that balance flexibility with interpretability. In our pursuit, we turn to Generalized Additive Models (GAMs), a widely used class of models known for their versatility …
abstract arxiv beyond biology chemistry cs.lg data discovery experimental explore form however physics regression relationships representation scientific scientific discovery stat.ml stress type
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