SimpliPy
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Related Articles from SNS
Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression
Announce Type: replace Abstract: Symbolic regression (SR) aims to discover interpretable analytical expressions that accurately describe observed data. Amortized SR promises to be much more efficient than the predominant genetic programming SR methods, but currently struggles to scale to realistic scientific complexity. We find that a key obstacle is the lack of a fast reduction of equivalent expressions to a concise normalized form.