awesome-TS-anomaly-detection VS pyod

What are some alternatives?

Awesome-Geospatial - Long list of geospatial tools and resources

tods - TODS: An Automated Time-series Outlier Detection System

openHistorian - The Open Source Time-Series Data Historian

isolation-forest - A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.

awesome-metric-learning - 😎 A curated list of awesome practical Metric Learning and its applications

alibi-detect - Algorithms for outlier, adversarial and drift detection

Netdata - The open-source observability platform everyone needs

pycaret - An open-source, low-code machine learning library in Python

NAB - The Numenta Anomaly Benchmark

anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

A3 - Inspired by recent advances in coverage-guided analysis of neural networks, we propose a novel anomaly detection method. We show that the hidden activation values contain information useful to distinguish between normal and anomalous samples. Our approach combines three neural networks in a purely data-driven end-to-end model. Based on the activation values in the target network, the alarm network decides if the given sample is normal. Thanks to the anomaly network, our method even works in strict semi-supervised settings. Strong anomaly detection results are achieved on common data sets surpassing current baseline methods. Our semi-supervised anomaly detection method allows to inspect large amounts of data for anomalies across various applications.

stumpy - STUMPY is a powerful and scalable Python library for modern time series analysis