Publikationen

In: IEEE Access, Vol. 10, Pages 1-10, IEEE, 2020.

In: 18th IEEE International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications (ICMLA-2019), December 16-19, Boca Raton, Florida, USA, Pages 561-566, ISBN 978-1-7281-4550-1, IEEE, 12/2019.

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In: ICANN. International Conference on Artificial Neural Networks (ICANN-2019), September 17-19, Munich, Germany, Pages 426-439, Vol. 11731, ISBN 978-3-030-30493-5, Springer, Cham, 9/2019.

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In: The 28th International Conference on Artificial Neural Networks. International Conference on Artificial Neural Networks (ICANN-2019), September 17-19, Munich, Germany, IEEE, 9/2019.

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In: Sensors - Open Access Journal (Sensors), Vol. 19, No. 11, Pages 1-15, MDPI, 5/2019.

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In: IEEE Access, Vol. 7, Pages 1991-2005, IEEE, 12/2018.

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In: Mark Last; Horst Bunke; Abraham Kandel (Hrsg.). Data Mining in Time Series and Streaming Databases. Chapter 7, Pages 144-168, Series in Machine Perception and Artificial Intelligence, Vol. 83, ISBN 978-981-3228-05-4, WORLD SCIENTIFIC, 3/2018.

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In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1802.02952, Pages 1-13, ArXiv, 2018.

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In: 2017 IEEE International Conference on Data Mining Workshops. IEEE International Conference on Data Mining Workshops (ICDMW-2017), November 18-21, New Orleans, LA, USA, Pages 1066-1073, ISBN 978-1-5386-3800-2, IEEE, 2017.

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Publikationen

Confident Classification using a Hybrid between Deterministic and Probabilistic Convolutional Neural Networks

A Comparative Analysis of Traditional and Deep Learning-based Anomaly Detection Methods for Streaming Data

TSXplain: Demystification of DNN Decisions for Time-Series Using Natural Language and Statistical Features

DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting

FuseAD: Unsupervised Anomaly Detection in Streaming Sensors Data by Fusing Statistical and Deep Learning Models

DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series

Data Analytics: Industrial Perspective & Solutions for Streaming Data

TSViz: Demystification of Deep Learning Models for Time-Series Analysis

Pattern-Based Contextual Anomaly Detection in HVAC Systems

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