DGLD
Graph anomaly detector
An open-source library for training and evaluating graph anomaly detection models
Deep Graph Outlier Detection
64 stars
2 watching
9 forks
Language: Python
last commit: over 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
| Detects anomalies in graph data using various algorithms | 1,350 |
| An end-to-end outlier detection system that integrates machine learning algorithms with database support | 252 |
| This repository provides code for training a model to detect anomalies in graph data using pattern mining and feature learning. | 40 |
| A toolbox for building and comparing graph neural network-based fraud detection models | 698 |
| Anomaly detection framework utilizing out-of-distribution data to improve deep learning model performance. | 548 |
| A Python framework for accelerating large-scale unsupervised outlier detection in heterogeneous datasets | 382 |
| A PyTorch implementation of a feature attribution technique using Wasserstein Generative Adversarial Networks for anomaly detection in medical images. | 93 |
| A toolbox for unsupervised graph-based fraud detection using multiple algorithms and techniques | 131 |
| A Python library for detecting outliers, adversarial examples, and data drift in various types of data | 2,262 |
| An automated system for detecting outliers in time-series data using machine learning algorithms and human expertise. | 1,484 |
| A MATLAB implementation of Support Vector Data Description (SVDD) for anomaly detection and classification. | 78 |
| A toolkit for rule-based and unsupervised anomaly detection in time series data | 1,108 |
| A benchmarking pipeline for evaluating anomaly detection methods on time series data using deep learning algorithms | 571 |
| An implementation of a graph neural network-based fraud detector designed to counter camouflaged fraudsters | 250 |
| A package providing functions to decompose and detect anomalies in time series data | 339 |