Network Analysis in Python

A library for graph deep learning research

🗡 A tool to visualize Dagger 2 dependency graphs

NetworKit is a growing open-source toolkit for large-scale network analysis.

An optimized graphs package for the Julia programming language

Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019

[EMNLP'2024] "OpenGraph: Towards Open Graph Foundation Models"

🔧 Python Random Graph Generator

Official Code Repository for the paper "Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations" (ICML 2022)

Exports task execution graph as .dot file

Generate graphs with gnuplot or matplotlib (Python) from sar data

Official repository for "Categorical Normalizing Flows via Continuous Transformations"

[TMLR] "GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?"

[ICLR 2024] "Latent 3D Graph Diffusion" by Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen

A library for graph analysis written Julia.

This repository contains PyTorch implementation of the following paper: "Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation"

DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data, IEEE BigData 2022

Implementation for the paper: GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation

MultiGraphGAN for predicting multiple target graphs from a source graph using geometric deep learning.

Awesome Graph Diffusion Models is a collection of graph generation works, including papers, codes and datasets.