Ptolemaic Indexing for Managing and Querying Internet of Things (IoT) Data. - Christian Beecks; Fabian Berns; Kjeld Willy Schmidt (IEEE BigData, 2019)

A New Approach for Efficient Structure Discovery in IoT. - Fabian Berns; Kjeld Willy Schmidt; Alexander Grass; Christian Beecks (IEEE BigData, 2019)

Gaussian Processes for Anomaly Description in Production Environments. - Christian Beecks; Kjeld Willy Schmidt; Fabian Berns; Alexander Graß (EDBT/ICDT Workshops, 2019)

V3C1 Dataset: An Evaluation of Content Characteristics. - Fabian Berns; Luca Rossetto; Klaus Schoeffmann; Christian Beecks; George Awad (ICMR, 2019)

lifeXplore at the Lifelog Search Challenge 2019. - Andreas Leibetseder; Bernd Münzer; Manfred Jürgen Primus; Sabrina Kletz; Klaus Schoeffmann; Fabian Berns; Christian Beecks (LSC@ICMR, 2019)

Automatic Gaussian Process Model Retrieval for Big Data. - Fabian Berns; Christian Beecks (CIKM, 2020)

Towards Large-scale Gaussian Process Models for Efficient Bayesian Machine Learning. - Fabian Berns; Christian Beecks (DATA, 2020)

Large-scale Retrieval of Bayesian Machine Learning Models for Time Series Data via Gaussian Processes. - Fabian Berns; Christian Beecks (KDIR, 2020)

Machine Learning for Storage Location Prediction in Industrial High Bay Warehouses. - Fabian Berns; Timo Ramsdorf; Christian Beecks (ICPR Workshops (4), 2020)

3CS Algorithm for Efficient Gaussian Process Model Retrieval. - Fabian Berns; Kjeld Schmidt; Ingolf Bracht; Christian Beecks (ICPR, 2020)

Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. - Fabian Berns; Markus Lange-Hegermann; Christian Beecks (IN4PL, 2020)

Automated Kernel Search for Gaussian Processes on Data Streams. - Jan David Hüwel; Fabian Berns; Christian Beecks (IEEE BigData, 2021)

LOGIC: Probabilistic Machine Learning for Time Series Classification. - Fabian Berns; Jan David Hüwel; Christian Beecks (ICDM, 2021)

On Kernel Search Based Gaussian Process Anomaly Detection. - Jan David Hüwel; Andreas Besginow; Fabian Berns; Markus Lange-Hegermann; Christian Beecks (IN4PL (Revised Selected Papers), 2021)

knowlEdge Project -Concept, Methodology and Innovations for Artificial Intelligence in Industry 4.0. - Sergio Álvarez-Napagao; Boki Ashmore; Marta Barroso; Cristian Barrué; Christian Beecks; Fabian Berns; Ilaria Bosi; Sisay Adugna Chala; Nicola Ciulli; Marta Garcia-Gasulla; Alexander Grass; Dimosthenis Ioannidis; et al. (INDIN, 2021)

Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes. - Fabian Berns; Christian Beecks (SDM, 2021)

Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data. - Fabian Berns; Christian Beecks (SDM, 2021)

Local Gaussian Process Model Inference Classification for Time Series Data. - Fabian Berns; Joschka Hannes Strueber; Christian Beecks (SSDBM, 2021)

Tracing Patterns in Electrophysiological Time Series Data. - Jan David Hüwel; Anne Gresch; Fabian Berns; Ruben Koch; Martina Düfer; Christian Beecks (DSAA, 2022)

Evaluating the Lottery Ticket Hypothesis to Sparsify Neural Networks for Time Series Classification. - Georg Stefan Schlake; Jan David Hüwel; Fabian Berns; Christian Beecks (ICDE Workshops, 2022)

A Comparative Performance Analysis of Fast K-Means Clustering Algorithms. - Christian Beecks; Fabian Berns; Jan David Hüwel; Andrea Linxen; Georg Stefan Schlake; Tim Düsterhus (iiWAS, 2022)

Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms. - Fabian Berns; Jan David Hüwel; Christian Beecks (SN Comput. Sci., 2022)

Machine Learning with Gaussian Processes: Automated Model Search and Data Analysis. - Fabian Berns (2022)

Trustworthy Medical Operational AI: Marrying AI and Regulatory Requirements. - Fabian Berns; Georg Zimmermann; Christian Borgelt; Niclas Heilig; Jan Kirchhoff; Florian Stumpe (IEEE Big Data, 2023)