These are my go-to libraries for Python data crunching.
cu-profiler is in active development. The default build profiles recorded Solana logs — deterministic, fast, CI-friendly, and the substrate the whole parser/report ...
Abstract: genetic programming (GP) is a widely recognized and powerful approach for symbolic regression (SR) problems. However, existing GP methods rely on a single form to solve the problem, which ...
This repository contains the code and data for the experiments in the paper "Discovering network dynamics with neural symbolic regression", published in Nature Computational Science (2025). Abstract: ...
Abstract: Physics-informed symbolic regression aims to recover explicit closed-form solutions of differential equations while preserving physical consistency. However, existing methods often suffer ...