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ORCIDXI-ML@KI 2020: Virtual Event / Bamberg, Germany
- Martin Atzmüller, Tomás Kliegr, Ute Schmid:
Proceedings of the First International Workshop on Explainable and Interpretable Machine Learning (XI-ML 2020) co-located with the 43rd German Conference on Artificial Intelligence (KI 2020), Bamberg, Germany, September 21, 2020 (Virtual Workshop). CEUR Workshop Proceedings 2796, CEUR-WS.org 2021 - Preface.
Invited talk
- Marcin P. Joachimiak:
How to Teach a Computer to Learn About Microbes: KG-COVID-19 and Microbial Graph Learning - Abstract.
Main Session
- Henrik Boström, Peter Höglund, Sven-Olof Junker, Ann-Sofie Öberg, Martin Sparr:
Explaining Multivariate Time Series Forecasts: An Application to Predicting the Swedish GDP. - Henrik Mucha, Sebastian Robert, Rüdiger Breitschwerdt, Michael Fellmann:
Towards Participatory Design Spaces for Explainable AI Interfaces in Expert Domains (Short Paper). - Kevin Volkert:
Teaching AI to Explain its Decisions Can Affect Class Balance. - Jürgen Fleiß, Elisabeth Bäck, Stefan Thalmann:
Explainability and the Intention to Use AI-based Conversational Agents (Short Paper). - Nico Potyka:
Foundations for Solving Classification Problems with Quantitative Abstract Argumentation. - Dennis Mollenhauer, Martin Atzmueller:
Sequential Exceptional Pattern Discovery Using Pattern-Growth: An Extensible Framework for Interpretable Machine Learning on Sequential Data. - Jia Sun, Tapabrata Chakraborti, J. Alison Noble:
A Comparative Study of Explainer Modules Applied to Automated Skin Lesion Classification.
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