TrustAGI-Lab/graph-deep-learning

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TrustAGI-Lab/graph-deep-learning

TrustAGI-Lab

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This repository summarises the open source codes of our group

Awesome-Graph-Neural-Networks

Paper Lists for Graph Neural Networks

graph_datasets

A Repository of Benchmark Graph Datasets for Graph Classification (31 Graph Datasets In Total).

ARGA

This is a TensorFlow implementation of the Adversarially Regularized Graph Autoencoder(ARGA) model as described in our paper: Pan, S., Hu, R., Long, G., Jiang, J., Yao, L., & Zhang, C. (2018). Adversarially Regularized Graph Autoencoder for Graph Embedding, [https://www.ijcai.org/proceedings/2018/0362.pdf].

SUBLIME

[WWW'22] Towards Unsupervised Deep Graph Structure Learning

CoLA

[TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning

TriDNR

Tri-Party Deep Network Representation, IJCAI-16

MTGODE

[TKDE 2022] The official PyTorch implementation of the paper "Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs".

UDAGCN

Python implementation of "Unsupervised Domain Adaptive Graph Convolutional Networks", WWW-20.

ANEMONE

[CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".

MERIT

[IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".

MGAE

Implementation of the CIKM-17 paper “MGAE: Marginalized Graph Autoencoder for Graph Clustering”

OpenWGL

OpenWGL: Open-World Graph Learning, ICDM-2020

MTG

Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification

BANE

BANE: Binarized Attributed Network Embedding - ICDM2018