Marwin Züfle

An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series

Norbert Schmitt, Johannes Grohmann, Nikolas Herbst, 2020, ICPE.

Best Practices for Time Series Forecasting (Tutorial)

André Bauer, Marwin Züfle, Samuel Kounev, 2019, 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W).

Utilizing Clustering to Optimize Resource Demand Estimation Approaches

Johannes Grohmann, Simon Eismann, Marwin Züfle, 2019, 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W).

Time Series Forecasting for Self-Aware Systems

Andreas Hotho, Albin Zehe, Nikolas Herbst, 2020, Proceedings of the IEEE.

A Survey on Predictive Maintenance for Industry 4.0 pdf

Dominik Schäfer, Marwin Züfle, Samuel Kounev, 2020, ArXiv.

Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field

Nikolas Herbst, Marwin Züfle, Samuel Kounev, 2020, 2020 IEEE 36th International Conference on Data Engineering (ICDE).

A Survey on Human Machine Interaction in Industry 4.0 pdf

Sebastian Müller, Dominik Schäfer, Marwin Züfle, 2020, ArXiv.

A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0

Samuel Kounev, Johannes Grohmann, Marwin Züfle, 2021, 2021 IEEE 19th International Conference on Industrial Informatics (INDIN).

Recommendations for Data-Driven Degradation Estimation with Case Studies from Manufacturing and Dry-Bulk Shipping

Samuel Kounev, Marwin Züfle, Marisa Mohr, 2021, RCIS.

Libra: A Benchmark for Time Series Forecasting Methods

Samuel Kounev, Nikolas Roman Herbst, Johannes Grohmann, 2021, ICPE.