Search Results for author: Daniel Seebacher

Found 2 papers, 1 papers with code

TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models

1 code implementation17 Sep 2021 Udo Schlegel, Duy Vo Lam, Daniel A. Keim, Daniel Seebacher

Time series forecasting is a demanding task ranging from weather to failure forecasting with black-box models achieving state-of-the-art performances.

Time Series Time Series Forecasting

MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales

no code implementations1 Sep 2020 Philipp Meschenmoser, Juri F. Buchmüller, Daniel Seebacher, Martin Wikelski, Daniel A. Keim

To close this gap, we present our MultiSegVA platform for interactively defining segmentation techniques and parameters on multiple temporal scales.

Clustering Segmentation +2

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