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Official repository for survey paper "Deep Graph Anomaly Detection: A Survey and New Perspectives", including diverse types of resources for graph anomaly detection.
A Library for Dynamic Graph Learning (NeurIPS 2023)
TGN for anomaly detection in DGraph-Fin dataset. (Top2 🥈 solution in DGraph-Fin Leaderboard) https://dgraph.xinye.com/
Passive DNS Dataset of Domain Resolutions
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
FedGraph (Federated Graph) is a library built upon PyTorch to easily train Graph Neural Networks (GNNs) under federated (distributed) setting.
Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models
"GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023
Official Implementations of "Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space""
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Pytorch implementation of paper 'GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks' to appear on WSDM2021
A collection of AWESOME things about Graph-Related LLMs.
The code of ICDM'21 paper "Deep Generation of Heterogeneous Networks"
Python package built to ease deep learning on graph, on top of existing DL frameworks.
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
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A Collection of Resources for Weakly-supervised Anomaly Detection (WSAD)
The official repository for ICDM 22' paper "Unsupervised Deep Subgraph Anomaly Detection"
PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)
Awesome Lists for Tenure-Track Assistant Professors and PhD students. (助理教授/博士生生存指南)
Diffusion model papers, survey, and taxonomy
A Python Library for Graph Outlier Detection (Anomaly Detection)
A sparsity aware implementation of "Biological Network Comparison Using Graphlet Degree Distribution" (Bioinformatics 2007)
PyTorch Implementation for "Deep Anomaly Detection on Attributed Networks" (SDM2019)
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…