merlerm/In-Context-Symbolic-Regression

Official code implementation for the ACL 2024 Student Research Workshop paper "In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery"

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Experimental

This tool helps researchers and scientists automatically discover mathematical formulas or equations that best describe a given set of numerical data. You input a dataset of numbers, and it iteratively suggests and refines potential mathematical expressions, eventually outputting the most accurate formula. It is ideal for anyone working with experimental data who needs to find underlying mathematical relationships without manually trying countless equations.

No commits in the last 6 months.

Use this if you have numerical data points and need to automatically identify the underlying mathematical function or formula that accurately models that data.

Not ideal if you need to understand causal relationships between variables or if your data cannot be represented by a mathematical function.

scientific-modeling experimental-data-analysis formula-discovery data-pattern-recognition equation-fitting
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 5 / 25

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Stars

17

Forks

1

Language

Python

License

MIT

Last pushed

Sep 26, 2024

Commits (30d)

0

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