qq-jiang's repositories
EvaluatingDPML
This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
EtherScamDB
Keep track of all current ethereum scams in a large database
MIA-GNN
Membership Inference Attack against Graph Neural Networks
LM_PersonalInfoLeak
The code and data for "Are Large Pre-Trained Language Models Leaking Your Personal Information?" (Findings of EMNLP '22)
FedGCN
Official Code for FedGCN [NeurIPS 2023]
lpgnet-prototype
A prototype implementation for Link Private Graph Network (LPGNet)
Rethinking-Anomaly-Detection
"Rethinking Graph Neural Networks for Anomaly Detection" in ICML 2022
HeteRobust-WWW22
How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)
HeteDP
Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation
Awesome-Deep-Graph-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 also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors
ADBench
Official Implement of "ADBench: Anomaly Detection Benchmark".
UTXO
Deciphering Bitcoin Blockchain Data by Cohort Analysis
privacy-preserving-gcn
Privacy-Preserving Graph Convolutional Networks for Text Classification
FedRecAttack
Model Poisoning Attack to Federated Recommendation
Meta-PN
PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)
ML-GCN
PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.
MIA_disparity
Code for paper: Understanding Disparate Effects of Membership Inference Attacks and Their Countermeasures
BlockSci
A high-performance tool for blockchain science and exploration
GraphLeaks
Code for the paper "Quantifying Privacy Leakage in Graph Embedding" published in MobiQuitous 2020