Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. - André Bauer 001; Mark Leznik; Michael Stenger; Robert Leppich; Nikolas Herbst; Samuel Kounev; Ian T. Foster (CoRR, 2023)

Comprehensive Exploration of Synthetic Data Generation: A Survey. - André Bauer 001; Simon Trapp; Michael Stenger; Robert Leppich; Samuel Kounev; Mark Leznik; Kyle Chard; Ian T. Foster (CoRR, 2024)

Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis. - Michael Stenger; André Bauer 001; Thomas Prantl; Robert Leppich; Nathaniel Hudson; Kyle Chard; Ian T. Foster; Samuel Kounev (ACM J. Data Inf. Qual., 2024)

Evaluation is key: a survey on evaluation measures for synthetic time series. - Michael Stenger; Robert Leppich; Ian T. Foster; Samuel Kounev; André Bauer 001 (J. Big Data, 2024)

TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and Imputation. - Robert Leppich; Michael Stenger; Daniel Grillmeyer; Vanessa Borst; Samuel Kounev (CoRR, 2025)

STEB: In Search of the Best Evaluation Approach for Synthetic Time Series. - Michael Stenger; Robert Leppich; André Bauer 001; Samuel Kounev (CoRR, 2025)

Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection. - Robert Leppich; Michael Stenger; André Bauer 001; Samuel Kounev (CoRR, 2025)