{"repo":"WassimTenachi/PhySO","free":true,"listed":false,"github":"https://github.com/WassimTenachi/PhySO","clone":"git clone https://github.com/WassimTenachi/PhySO.git","description":"Physical Symbolic Optimization","language":"Python","stars":1970,"topics":["deep-learning","machine-learning","physics","python","reinforcement-learning","symbolic-regression","equation-discovery"],"license":"MIT","category":"machine-learning","readme_excerpt":"$\\Phi$-SO : Physical Symbolic Optimization Physical symbolic optimization ( $\\Phi$-SO ) - A symbolic optimization package built for physics. Source code: WassimTenachi/PhySO\\ Documentation: physo.readthedocs.io What's New ✨ 2025-08 : 📦 Install via pip install physo and conda now available! 2025-07 : 🐍 Python 3.12 + latest NumPy / PyTorch / SymPy support. 2024-06 : 📚 Full documentation overhaul. 2024-05 : 🔬 Class SR : Multi-dataset symbolic regression. 2024-02 : 🎯 Uncertainty-aware fitting. 2023-08 : ⚡ Dimensional analysis acceleration. 2023-03 : 🌟 PhySO initial release (physics-focused SR). Highlights $\\Phi$-SO's symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms. physo is able to leverage: Physical units constraints, reducing the search space with dimensional analysis ([[Tenachi et al 2023]](https://arxiv.org/abs/2303.03192)) Class constraints, searching for a single analytical functional form that accurately fits multiple datasets - each governed by its own (possibly) unique set of fitting parameters ([[Tenachi et al 2024]](https://arxiv.org/abs/2312.01816)) $\\Phi$-SO recovering the equation for a damped harmonic oscillator: https://github.com/WassimTenachi/PhySO/assets/63928316/655b0eea-70ba-4975-8a80-00553a6e2786 Performances on the standard Feynman benchmark from SRBench) comprising 120 expressions from the Feynman Lectures on Physics against popular SR packa","default_branch":null,"files":null,"tree":[],"storefront":"/r/WassimTenachi","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/WassimTenachi/PhySO/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}