2021
Temporal convolutional autoencoder for unsupervised anomaly detection in time series Journal Article
In: Applied Soft Computing, vol. 112, S. 107751, 2021.
2020
Time Series Encodings with Temporal Convolutional Networks Proceedings Article
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.
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.
2019
Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks Proceedings Article
In: Barancíková, Petra; Holena, Martin; others, (Hrsg.): Proc. 19th Conference Information Technologies - Applications and Theory (ITAT 2019), 2019, (Best Paper Award).
2018
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).
2017
Anomaly Detection in Time Series with Discrete Wavelet Transforms and Maximum Likelihood Estimation Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 27. Workshop Computational Intelligence, S. 67-71, Universitätsverlag Karlsruhe, 2017.
Time Series Anomaly Detection with Discrete Wavelet Transforms and Maximum Likelihood Estimation Proceedings Article
In: Valenzuela, Olga; Rojas, Ignacio; others, (Hrsg.): International Work-Conference on Time Series (ITISE2017), 2017.
Online anomaly detection on the Webscope S5 dataset: A comparative study Proceedings Article
In: IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017), S. 1, Springer 2017.
Suchfeld
Machine Learning and Deep Learning Approaches for Multivariate Time Series Prediction and Anomaly Detection PhD Thesis
Leiden University and TH Köln, 2022, (PhD thesis).
Temporal convolutional autoencoder for unsupervised anomaly detection in time series Journal Article
In: Applied Soft Computing, vol. 112, S. 107751, 2021.
Time Series Encodings with Temporal Convolutional Networks Proceedings Article
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.
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.
Anomaly Detection in Electrocardiogram Readings with Stacked LSTM Networks Proceedings Article
In: Barancíková, Petra; Holena, Martin; others, (Hrsg.): Proc. 19th Conference Information Technologies - Applications and Theory (ITAT 2019), 2019, (Best Paper Award).
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).
Anomaly Detection in Time Series with Discrete Wavelet Transforms and Maximum Likelihood Estimation Proceedings Article
In: Hoffmann, Frank; Hüllermeier, Eyke (Hrsg.): Proceedings 27. Workshop Computational Intelligence, S. 67-71, Universitätsverlag Karlsruhe, 2017.
Time Series Anomaly Detection with Discrete Wavelet Transforms and Maximum Likelihood Estimation Proceedings Article
In: Valenzuela, Olga; Rojas, Ignacio; others, (Hrsg.): International Work-Conference on Time Series (ITISE2017), 2017.
Online anomaly detection on the Webscope S5 dataset: A comparative study Proceedings Article
In: IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017), S. 1, Springer 2017.