2 papers
cs.AI2025
Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection
Robert Leppich, Michael Stenger, André Bauer +1
With the advent of Transformers, time series forecasting has seen significant advances, yet it remains challenging due to the need for effective sequence representation, memory con…
cs.LG2025
STEB: In Search of the Best Evaluation Approach for Synthetic Time Series
Michael Stenger, Robert Leppich, André Bauer +1
The growing need for synthetic time series, due to data augmentation or privacy regulations, has led to numerous generative models, frameworks, and evaluation measures alike. Objec…