High-Performance Symbolic Regression in Python and Julia

Physical Symbolic Optimization

Distributed High-Performance Symbolic Regression in Julia

[ICLR 2025 Oral] This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with Large Language Models

Encoding physics to learn reaction-diffusion processes

A benchmark suite for evaluating LLM-based interactive scientific reasoning.

[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"

Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"

EPDE - partial differential equations discovery framework

An approach for embedding hierarhical structures into a continuous vector space using variational autoencoders.

[ICLR 2024 Spotlight] SNIP on Symbolic Regression: Deep Symbolic Regression with Multimodal Pretraining

Extremly fast c++/python symbolic regression library based on parallel local search.

PSRN (Parallel Symbolic Regression Network) enhanced SymbolicRegression.jl via fast, large-scale parallel symbolic evaluations on GPUs

Toolkit for symbolic regression/equation discovery

Benchmarks robust equation discovery from noisy data via synthetic ODE/PDE datasets and automated method comparison

Physics-informed refinement learning for equation discovery

Fast Amortized Neural Symbolic Regression with Transformers and SimpliPy

Advanced Machine Learning

This repository contains the codes for framework for equation discovery by combining Neural Networks with Characteristic Curves (NN-CC), Symmetry Constraints, and Post-Symbolic Regression (Post-SR). It also incorporates implementations of SINDy and pySR within the CC-based formalism.

A repository for the Behaviour-aware Equation distance measure