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cs.LG2025
CLaP -- State Detection from Time Series
Arik Ermshaus, Patrick Schäfer, Ulf Leser
The ever-growing amount of sensor data from machines, smart devices, and the environment leads to an abundance of high-resolution, unannotated time series (TS). These recordings en…
cs.LG2024
Discovering Leitmotifs in Multidimensional Time Series
Patrick Schäfer, Ulf Leser
A leitmotif is a recurring theme in literature, movies or music that carries symbolic significance for the piece it is contained in. When this piece can be represented as a multi-d…
cs.LG2023
Raising the ClaSS of Streaming Time Series Segmentation
Arik Ermshaus, Patrick Schäfer, Ulf Leser
Ubiquitous sensors today emit high frequency streams of numerical measurements that reflect properties of human, animal, industrial, commercial, and natural processes. Shifts in su…