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awesome-community-detection

A curated list of community detection research papers with implementations.

awesome-gnn4ts

Awesome resources related to GNNs for Time Series Analysis (GNN4TS) 🔥 https://arxiv.org/abs/2307.03759

awesome-graph-llm

A collection of AWESOME things about Graph-Related LLMs.

awesome-graph-transformer

Papers about graph transformers.

awesome-influence-maximization-papers

awesome-ml4co

Awesome machine learning for combinatorial optimization papers.

basicsirmodel

A simple SIR model in Python

care-gnn

Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

colge

cs193p-2017-fall-demo-and-solution

it's slides demo and solutions of assignments of cs193p 2017 fall

deep-learning-books

Books for machine learning, deep learning, math, NLP, CV, RL, etc. 一些机器学习、深度学习等相关话题的书籍。

deepim

design-resource

A list of design resources.

designers-learn-git

为设计师而作的GitHub的快速学习教程

dl4disassortativegraphs

Papers about developing DL methods on disassortative graphs

ea-gnn

easy-rl

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

eco-dqn

Implementation of ECO-DQN as reported in "Exploratory Combinatorial Optimization with Reinforcement Learning".

epimodel

Mathematical Modeling of Infectious Disease Dynamics

gem

geom-gcn

getoldtweets-python

A project written in Python to get old tweets, it bypass some limitations of Twitter Official API.

gnnpapers

Must-read papers on graph neural networks (GNN)

gnnrl

gradient_decent

graph-llm

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

graph-reinforcement-learning-literature

This open source library is available to summarize several years of research papers on graph reinforcement learning for the convenience of researchers

graph-reinforcement-learning-papers

A curated list of graph reinforcement learning papers.

graph-theory

Julia and Python complex system applications in ecology, epidemiology, sociology, economics & finance; network science models including Erdős-Rényi & Barabási-Albert; graph theory algorithms involving Gillespie, Bron Kerbosch, Bellman Ford, A*, Kruskal, Borůvka, Prim, Dijkstra, Topological Sort, DFS, BFS

graphgym

Platform for designing and evaluating Graph Neural Networks (GNN)