Symbolic Regression

2 items

RESEARCHarXiv CS.LG·1d ago

Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression

Symbolic regression (SR) explores mathematical functions to capture relationships in datasets, but its adoption is limited by a lack of uncertainty quantification (UQ). This survey is the first to address UQ in SR, reviewing current literature across frequentist, Bayesian, and model selection approaches.

Uncertainty Quantification machine learning Regression Analysis Symbolic Regression

RESEARCHarXiv CS.AI·5/6/2026

Programmatic Context Augmentation for LLM-based Symbolic Regression

This paper introduces a novel LLM-based evolutionary search framework for symbolic regression, addressing the limitations of existing methods that rely solely on scalar evaluation metrics. It incorporates programmatic context augmentation to enable code-based data analysis and richer information extraction, aiming to improve the discovery of mathematical expressions.

Data Analysis Symbolic Regression AI Research LLM