douzhenxing

Joint_Supervised_Learning_for_SR

[ICLR 2023]This repository contains the official Pytorch implementation for the paper "T-JSL: Transformer-based model for symbolic regression via joint supervised learning"

symbolicregression

SR based on LLMs.

DySymNet

[ICML 2024] Official Pytorch implementation of the paper "A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data"

flow-gan

Code for "Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models", AAAI 2018.

srbench

A living benchmark framework for symbolic regression

gplearn

Genetic Programming in Python, with a scikit-learn inspired API

pdenetgen

Python package for NN generation from physics

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

sympde

Symbolic calculus for partial differential equations (and variational forms)

PDE-Net

PDE-Net: Learning PDEs from Data

PySR

High-Performance Symbolic Regression in Python and Julia

AI-Feynman

dPads

NeurIPS'21 Differentiable Program Synthesis

SP-GPSR

Genetic Programming Symbolic Regression with Simplification-Pruning Operator for Solving Differential Equations

deep-symbolic-optimization

A deep learning framework for symbolic optimization.

DISCOVER

Deep identification of symbolic open-form PDEs via enhanced reinforcement-learning

DK-for-TST

This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).

torch-two-sample

A PyTorch library for two-sample tests

HoeffdingD

Efficient implementation of Hoeffding Distance in Python for large datasets

deepxde

A library for scientific machine learning and physics-informed learning

PINNs

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

DeePyMoD

poseidon

Code for the paper "Poseidon: Efficient Foundation Models for PDEs"

AIM

Code for the paper: Adversarial Inference by Matching priors and conditionals

DDKS

A high-dimensional Kolmogorov-Smirnov distance for comparing high dimensional distributions

nflows

Normalizing flows in PyTorch

zuko

Normalizing flows in PyTorch

Residual-Flow

An implementation of the Residual Flow algorithm for out-of-distribution detection.

ddpm-pytorch

这个是一个ddpm的pytorch仓库，可以用于训练自己的数据集。

pytorch-ddpm

Unofficial PyTorch implementation of Denoising Diffusion Probabilistic Models