no code implementations • 1 Jan 2021 • Hiba Arnout, Johanna Bronner, Thomas Runkler
We prove that our model outperforms the state-of-the-art generative models and leads to a significant and consistent improvement in the quality of the generated time series while at the same time preserving the classes and the variation of the original dataset.
no code implementations • 23 Dec 2019 • Hiba Arnout, Johannes Kehrer, Johanna Bronner, Thomas Runkler
This is particularly true when parts of the training data have been artificially generated to overcome common training problems such as lack of data or imbalanced dataset.
no code implementations • 16 Sep 2019 • Udo Schlegel, Hiba Arnout, Mennatallah El-Assady, Daniela Oelke, Daniel A. Keim
In this work, we apply XAI methods previously used in the image and text-domain on time series.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +2