Keplearn reports equation recovery gains with limited curve-fitting performance

Keplearn, an MIT-licensed tool that searches measurement tables for mathematical equations, reports recovering exact symbolic solutions on 64.7% of 116 noise-free Feynman benchmark datasets. Its project documentation compares that result with AIFeynman's published 55.8% rate. The Rust program uses recursive mathematical transformations and checks candidate equations against held-out data. Binaries are available for macOS, Windows and Linux. The reported benchmark used one trial per dataset and a 60-second fitting budget. Performance deteriorated with noise, and median test R2 was about -0.003 across 138 datasets without known closed-form equations.