109 Open source projects that are alternatives of or similar to GNN4CD

Implementation of "Overlapping Community Detection with Graph Neural Networks"

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Subgraph Neural Networks (NeurIPS 2020)

Code and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"

Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba 来自阿里巴巴的一站式大规模图计算系统 图分析 图查询 图机器学习

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

Probabilistic Type Inference using Graph Neural Networks

AAAI'21: Data Augmentation for Graph Neural Networks

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

Visualization tool for Graph Neural Networks

A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).

A curated list of awesome graph & self-supervised-learning-based recommendation.

Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Summary of social recommendation papers and codes

Tutorials for Machine Learning on Graphs

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Representing Long-Range Context for Graph Neural Networks with Global Attention

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

Overlapping community detection in Large-Scale Networks using BigCLAM model build on Apache Spark

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

Representation Learning on Graphs with Jumping Knowledge Networks

An implementation of "Community Preserving Network Embedding" (AAAI 2017)

Demo of RouteNet in ACM SIGCOMM'19

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

Pytorch differentiable molecular dynamics

Message Passing Neural Networks for Simplicial and Cell Complexes

source code for signed graph attention networks (ICANN2019) & SDGNN (AAAI2021)

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

Locally Private Graph Neural Networks (ACM CCS 2021)

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

A spherical CNN for weather forecasting

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

This is a Pytorch implementation of GraphLIME

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

Reimplementation of Graph Embedding methods by Pytorch.

Code and resources on scalable and efficient Graph Neural Networks

Graph-based machine learning for chemical property prediction

GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

An index of recommendation algorithms that are based on Graph Neural Networks.

Material for the EPFL master course "A Network Tour of Data Science", edition 2019.

[ACL 2021] KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

Awesome Graph Self-Supervised Learning

A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017).

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

Geometric Deep Learning for Flux

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021