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2021

Thill, Markus; Konen, Wolfgang; Wang, Hao; Bäck, Thomas

Temporal convolutional autoencoder for unsupervised anomaly detection in time series Journal Article

In: Applied Soft Computing, 112 , S. 107751, 2021.

Links | BibTeX | Schlagwörter: anomaly detection, deep learning, TCN, time series

2020

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Time Series Encodings with Temporal Convolutional Networks Inproceedings

In: Vasile, Massimiliano; Filipic, Bogdan (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA), Bruxelles. Video (15 min) available at https://youtu.be/PjI4fpcTGFY, 2020.

Links | BibTeX | Schlagwörter: anomaly detection, deep learning, TCN, time series

Thill, Markus; Konen, Wolfgang

Predictive Maintenance & Anomalie-Erkennung: Effiziente Instandhaltung mit Verfahren der KI Miscellaneous

Vortrag DEBRL2020 (Digital Exchange Bergisches Rheinland 2020), als Video über https://digital-xchange.de/streaming verfügbar, 2020.

Links | BibTeX | Schlagwörter: anomaly detection, deep learning, TCN, time series

2019

Thill, Markus; Däubner, Sina; Konen, Wolfgang; Bäck, Thomas

Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks Inproceedings

In: Barancíková, Petra; Holena, Martin; others, (Hrsg.): Proc. 19th Conference Information Technologies - Applications and Theory (ITAT 2019), 2019, (Best Paper Award).

Links | BibTeX | Schlagwörter: anomaly detection, deep learning, learning, LSTM, time series

2018

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Online Adaptable Time Series Anomaly Detection with Discrete Wavelet Transforms and Multivariate Gaussian Distributions Technical Report

Research Center CIOP (Computational Intelligence, Optimization and Data Mining) TH Köln - University of Applied Science, 2018, (submitted to Archives of Data Sciences, Series A (ECDA'2018), preprint available at http://www.gm.fh-koeln.de/ciopwebpub/Thill18a.d/AoDS2018.pdf).

Links | BibTeX | Schlagwörter: anomaly detection, DWT, maximum likelihood estimation, time series, wavelet transform

2017

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Anomaly Detection in Time Series with Discrete Wavelet Transforms and Maximum Likelihood Estimation Inproceedings

In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 27. Workshop Computational Intelligence, S. 67-71, Universitätsverlag Karlsruhe, 2017.

Links | BibTeX | Schlagwörter: anomaly detection, DWT, time series

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Time Series Anomaly Detection with Discrete Wavelet Transforms and Maximum Likelihood Estimation Inproceedings

In: Valenzuela, Olga; Rojas, Ignacio; others, (Hrsg.): International Work-Conference on Time Series (ITISE2017), 2017.

Links | BibTeX | Schlagwörter: anomaly detection, DWT, time series

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Online anomaly detection on the Webscope S5 dataset: A comparative study Inproceedings

In: IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017), S. 1, Springer 2017.

Links | BibTeX | Schlagwörter: anomaly detection, time series

 


Suchfeld

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1.

Thill, Markus

Machine Learning and Deep Learning Approaches for Multivariate Time Series Prediction and Anomaly Detection PhD Thesis

Leiden University and TH Köln, 2022, (PhD thesis).

BibTeX

2.

Thill, Markus; Konen, Wolfgang; Wang, Hao; Bäck, Thomas

Temporal convolutional autoencoder for unsupervised anomaly detection in time series Journal Article

In: Applied Soft Computing, 112 , S. 107751, 2021.

Links | BibTeX

3.

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Time Series Encodings with Temporal Convolutional Networks Inproceedings

In: Vasile, Massimiliano; Filipic, Bogdan (Hrsg.): 9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA), Bruxelles. Video (15 min) available at https://youtu.be/PjI4fpcTGFY, 2020.

Links | BibTeX

4.

Thill, Markus; Konen, Wolfgang

Predictive Maintenance & Anomalie-Erkennung: Effiziente Instandhaltung mit Verfahren der KI Miscellaneous

Vortrag DEBRL2020 (Digital Exchange Bergisches Rheinland 2020), als Video über https://digital-xchange.de/streaming verfügbar, 2020.

Links | BibTeX

5.

Thill, Markus; Däubner, Sina; Konen, Wolfgang; Bäck, Thomas

Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks Inproceedings

In: Barancíková, Petra; Holena, Martin; others, (Hrsg.): Proc. 19th Conference Information Technologies - Applications and Theory (ITAT 2019), 2019, (Best Paper Award).

Links | BibTeX

6.

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Online Adaptable Time Series Anomaly Detection with Discrete Wavelet Transforms and Multivariate Gaussian Distributions Technical Report

Research Center CIOP (Computational Intelligence, Optimization and Data Mining) TH Köln - University of Applied Science, 2018, (submitted to Archives of Data Sciences, Series A (ECDA'2018), preprint available at http://www.gm.fh-koeln.de/ciopwebpub/Thill18a.d/AoDS2018.pdf).

Links | BibTeX

7.

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Anomaly Detection in Time Series with Discrete Wavelet Transforms and Maximum Likelihood Estimation Inproceedings

In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 27. Workshop Computational Intelligence, S. 67-71, Universitätsverlag Karlsruhe, 2017.

Links | BibTeX

8.

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Time Series Anomaly Detection with Discrete Wavelet Transforms and Maximum Likelihood Estimation Inproceedings

In: Valenzuela, Olga; Rojas, Ignacio; others, (Hrsg.): International Work-Conference on Time Series (ITISE2017), 2017.

Links | BibTeX

9.

Thill, Markus; Konen, Wolfgang; Bäck, Thomas

Online anomaly detection on the Webscope S5 dataset: A comparative study Inproceedings

In: IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017), S. 1, Springer 2017.

Links | BibTeX