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CITATION.cff
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cff-version: 1.2.0
title: ADEPT
message: "If you use this software, please cite it as below."
type: software
authors:
- given-names: Benedikt Tobias
family-names: Müller
orcid: 'https://orcid.org/0000-0003-4945-6546'
- given-names: Janis
family-names: Büse
orcid: 'https://orcid.org/0000-0002-2247-0906'
- given-names: Marvin
family-names: Ender
repository-code: 'https://github.com/ADEPT-ML/Server'
url: 'https://github.com/ADEPT-ML'
abstract: >-
ADEPT is a framework for detecting anomalies in energy
consumption data. As such, it includes interfaces for
processing user time series data and can be used to
interactively visualize explanatory information about
anomalies. ADEPT features several shallow and deep machine
learning algorithms for anomaly detection and explanation.
keywords:
- machine learning
- anomaly detection
- explainability
- dashboard
license: Apache-2.0