Author

Frank Hutter

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#machine learning Preprint Oct 2026

Improving Neural Symbolic Regression with a Diverse Prior and Post-training Alignment

Symbolic regression is the problem of finding an expression that fits a dataset. Solving it requires searching a combinatorial space of candidate expressions. Neural symbolic regression can amortize that search by training a model once on synthetic data and then predicting expressions for a new dataset. But existing mo...

Dave Otte, J. Franke, Frank Hutter · 0 citations