Fabian Berns

PhD thesis, 2022

Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms.

[BibT_eX]

[DOI]

SN Comput. Sci., 2022

A Comparative Performance Analysis of Fast K-Means Clustering Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Information Integration and Web Intelligence, 2022

Evaluating the Lottery Ticket Hypothesis to Sparsify Neural Networks for Time Series Classification.

[BibT_eX]

[DOI]

Proceedings of the 38th IEEE International Conference on Data Engineering Workshops, 2022

Tracing Patterns in Electrophysiological Time Series Data.

[BibT_eX]

[DOI]

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

2021

Local Gaussian Process Model Inference Classification for Time Series Data.

[BibT_eX]

[DOI]

Joschka Hannes Strüber

Proceedings of the SSDBM 2021: 33rd International Conference on Scientific and Statistical Database Management, 2021

Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data.

[BibT_eX]

[DOI]

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

knowlEdge Project -Concept, Methodology and Innovations for Artificial Intelligence in Industry 4.0.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on Industrial Informatics, 2021

On Kernel Search Based Gaussian Process Anomaly Detection.

[BibT_eX]

[DOI]

Andreas Besginow

Markus Lange-Hegermann

Proceedings of the Innovative Intelligent Industrial Production and Logistics, 2021

LOGIC: Probabilistic Machine Learning for Time Series Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2021

Automated Kernel Search for Gaussian Processes on Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0.

[BibT_eX]

[DOI]

Markus Lange-Hegermann

Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics, 2020

3CS Algorithm for Efficient Gaussian Process Model Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Machine Learning for Storage Location Prediction in Industrial High Bay Warehouses.

[BibT_eX]

[DOI]

Timo Ramsdorf

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Large-scale Retrieval of Bayesian Machine Learning Models for Time Series Data via Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 12th International Joint Conference on Knowledge Discovery, 2020

Towards Large-scale Gaussian Process Models for Efficient Bayesian Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Data Science, 2020

Automatic Gaussian Process Model Retrieval for Big Data.

[BibT_eX]

[DOI]

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

lifeXplore at the Lifelog Search Challenge 2019.

[BibT_eX]

[DOI]

Andreas Leibetseder

Bernd Münzer

Manfred Jürgen Primus

Proceedings of the ACM Workshop on Lifelog Search Challenge, 2019

V3C1 Dataset: An Evaluation of Content Characteristics.

[BibT_eX]

[DOI]

Proceedings of the 2019 on International Conference on Multimedia Retrieval, 2019

Gaussian Processes for Anomaly Description in Production Environments.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference, 2019

A New Approach for Efficient Structure Discovery in IoT.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Ptolemaic Indexing for Managing and Querying Internet of Things (IoT) Data.

[BibT_eX]

[DOI]