In our work we present a benchmark dataset for learning forecasts of dynamical systems on non-grid structured data
moreNews - Data Science Chair
In our paper we propose a method allowing the comparison of human behaviour across behavioural networks with different properties.
moreDr Anna Krause is co-organizing the workshop "Neuro-Explicit AI and Expert-Informed Machine Learning for Engineering and Physical Sciences (ExML)" at ECMLPKDD 2023.
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In our paper, we conduct an initial study to investigate the use of audio data from the We4Bee project in detecting bee swarming.
moreCAIDAS at the ai.bay 2023
02/28/2023
Über die Zukunft von Sprachassistenten und die Herausforderungen neuer Technologien sowie das Projekt "MOTIV" sprachen Professorin Carolin Wienrich und Professor Andreas Hotho mit dem Bayerische Forschungsinstitut für Digitale Transformation (bidt).
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In our work we review existing approaches that explain AI-based anomaly detectors by highlighting features relevant for their predictions.
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Carolin Wienrich, Marc Latoschik, and Andreas Hotho visited the Bavarian Digital Summit. In the evening, they were invited to the reception of State Minister Judith Gerlach.
moreThe MAGNET4Cardiac7T project will be funded.
11/15/2022
The final decision is out! The MAGNET4Cardiac7T project will be funded. The official start is on the 01.12.2022. Within the project a method for modelling the distribution of electromagnetic fields in a human thorax while using a MRT-Scanner will be developed.
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In this paper by M. Steininger et al., deep learning helps to improve climate models by post-processing their outputs.
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