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15 search results found

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

Awesome Fraud Detection Papers ⭐ 1,364

A curated list of data mining papers about fraud detection.

Graph Fraud Detection Papers ⭐ 1,148

A curated list of graph-based fraud, anomaly, and outlier detection papers & resources

Pygod ⭐ 1,138

A Python Library for Graph Outlier Detection (Anomaly Detection)

Awesome Deep Graph Anomaly Detection ⭐ 215

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 and boost further research in this area.

Care Gnn ⭐ 127

Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

Fraud Detection Using Machine Learning ⭐ 98

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Fraud Detection Papers ⭐ 45

Learning Fraud Detection from research papers and industry applications.

Predict Fraud Using Auto Ai ⭐ 28

Use AutoAI to detect fraud

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Fraud Detection In Online Transactions ⭐ 23

Detecting Frauds in Online Transactions using Anamoly Detection Techniques Such as Over Sampling and Under-Sampling as the ratio of Frauds is less than 0.00005 thus, simply applying Classification Algorithm may result in Overfitting

Pump And Dump Detection On Cryptocurrency ⭐ 20

Sequence-based Target Coin Prediction for Cryptocurrency Pump-and-Dump (SIGMOD 23)

A PyTorch implementation of the ACM SIGKDD 2021 paper titled "PETGEN: Personalized Text Generation Attack on Deep Sequence Embedding-based Classification Models"

Frauddetection ⭐ 11

Examples and Tutorials related to fraud detection with machine learning and deep learning

Projects ⭐ 10

This is the repository containing machine learning and deep learning projects, as well as some presentation slides on these topics.

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