Seondong / Customs-Fraud-Detection
Simulation framework for customs fraud detection using import declarations.
☆30Updated 2 years ago
Alternatives and similar repositories for Customs-Fraud-Detection:
Users that are interested in Customs-Fraud-Detection are comparing it to the libraries listed below
- This repository contains the code used in the experimental setup of the paper 'Inductive Graph Representation Learning for Fraud Detectio…☆33Updated last year
- DATE: Dual Attentive Tree-aware Embedding for Customs Frauds Detection☆62Updated 3 years ago
- Colab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend.☆40Updated 3 years ago
- Multi-GNN architectures for Anti-Money Laundering.☆75Updated last year
- A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X☆131Updated 3 years ago
- TNNLS: A Synergistic Approach for Graph Anomaly Detection with Pattern Mining and Feature Learning; CIKM'20: Error-bounded Graph Anomaly …☆42Updated last year
- The official implementation of the DGA-GNN algorithm.☆24Updated 9 months ago
- Anti Money Laundering Detection using Graph Attention Network☆46Updated last year
- Fraud detection using Graph Convolutional Networks☆11Updated 2 years ago
- Interaction-Focused Anomaly Detection on Bipartite Node-and-Edge-Attributed Graphs☆13Updated last year
- ☆34Updated 2 years ago
- Repository for Fraud Dataset Benchmark☆175Updated last year
- Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"☆35Updated last year
- A Pytorch implement of paper "Anomaly detection in dynamic graphs via transformer" (TADDY).☆57Updated 3 years ago
- (WWW 2021) Source code of PC-GNN☆104Updated 3 years ago
- Fraud detection in bank transactions using graph databases and machine learning.☆21Updated 5 years ago
- Fraud Detection, Low Homophily, Label Utilization, Graph Mining☆49Updated last year
- Resources and environment for unsupervised outlier model selection (UOMS)☆23Updated 2 years ago
- ☆67Updated last year
- Materials for SDM 2023 tutorial: Augmentation Methods for Graph Learning☆21Updated 2 years ago
- A curated list of publications and code about data augmentaion for graphs.☆64Updated 2 years ago
- Contrastive Attributed Network Anomaly Detection with Data Augmentation (PAKDD'22)☆26Updated 2 years ago
- ☆38Updated 2 years ago
- ☆29Updated last year
- Code of the paper 'Raising the Bar in Graph-level Anomaly Detection' published in IJCAI-2022☆24Updated 2 years ago
- Code Repository for Paper "HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks"☆11Updated last year
- ☆22Updated last year
- A collection of papers for graph anomaly detection, and published algorithms and datasets.☆123Updated last year
- [CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".☆49Updated 3 years ago
- [WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction☆43Updated 5 months ago