Keplearn open-sources a deterministic symbolic regression engine
What happened
On October 29, Hacker News' front page featured Keplearn, a deterministic symbolic regression engine written in Rust that recovers closed-form equations from tabular data, often solving exact patterns in milliseconds. In the reported benchmark, on SRBench's Feynman dataset with zero noise, Keplearn reached a 64.7% symbolic solve rate, above the 55.8% AIFeynman has published. The tool is MIT-licensed and ships as a single zero-dependency static binary for macOS, Windows and Linux.
Written by AI from the coverage · updated 1 hour ago
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- Hacker News front pageKeplearn: Extract Equations from Data in Seconds
Keplearn 是一个用 Rust 编写的确定性符号回归引擎，可从表格数据中恢复闭式方程，精确规律通常在毫秒级解出。在 SRBench 基准上，Feynman 数据集零噪声下的符号解率为 64.7%，高于 AIFeynman 已公布的 55.8%。该工具以单一静态二进制发布、零依赖，采用 MIT 许可证，支持 macOS、Windows 和 Linux。
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