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Stars
An orchestration platform for the development, production, and observation of data assets.
An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted by AAAI 2023.
The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
We have established a Chinese knowledge graphic in the field of education in an open way
[TKDE 2021] A PyTorch implementation of "Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection".
rvbugs0 / CoLA
Forked from TrustAGI-Lab/CoLAAnomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (CoLA), TNNLS-21
TKDE'22-GraphCAD: https://arxiv.org/pdf/2108.07516.pdf
This is a repository contaning baseline code for DGraphFin Dataset
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks
[TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
[CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
GH Archive is a project to record the public GitHub timeline, archive it, and make it easily accessible for further analysis.
A Python Library for Graph Outlier Detection (Anomaly Detection)
Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We…
PyTorch Implementation for "Deep Anomaly Detection on Attributed Networks" (SDM2019)
Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge (ACL 2021)
Pytorch implementation of "Graph Convolutional Networks for Text Classification"
Python package built to ease deep learning on graph, on top of existing DL frameworks.
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
Official implementation of NeurIPS'21 paper"Motif-based Graph Self-Supervised Learning for Molecular Property Prediction"