Group Anomaly Detection

3 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Group Anomaly Detection using Deep Generative Models

raghavchalapathy/gad 13 Apr 2018

Unlike conventional anomaly detection research that focuses on point anomalies, our goal is to detect anomalous collections of individual data points.

MSTREAM: Fast Anomaly Detection in Multi-Aspect Streams

Stream-AD/MStream 17 Sep 2020

Given a stream of entries in a multi-aspect data setting i. e., entries having multiple dimensions, how can we detect anomalous activities in an unsupervised manner?

Isolation Distributional Kernel: A New Tool for Point & Group Anomaly Detection

IsolationKernel/Codes 24 Sep 2020

Existing approaches based on kernel mean embedding, which convert a point kernel to a distributional kernel, have two key issues: the point kernel employed has a feature map with intractable dimensionality; and it is {\em data independent}.