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) - researchr publication

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Martin Atzmüller, Tomás Kliegr, Ute Schmid, editors, 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). Volume 2796 of CEUR Workshop Proceedings, CEUR-WS.org, 2021. [doi]

Conference: ki2021

Abstract is missing.

Explainability and the Intention to Use AI-based Conversational Agents (Short Paper)Jürgen Fleiß, Elisabeth Bäck, Stefan Thalmann. [doi]

A Comparative Study of Explainer Modules Applied to Automated Skin Lesion ClassificationJia Sun, Tapabrata Chakraborti, J. Alison Noble. [doi]

Teaching AI to Explain its Decisions Can Affect Class BalanceKevin Volkert. [doi]

Sequential Exceptional Pattern Discovery Using Pattern-Growth: An Extensible Framework for Interpretable Machine Learning on Sequential DataDennis Mollenhauer, Martin Atzmueller. [doi]

Explaining Multivariate Time Series Forecasts: An Application to Predicting the Swedish GDPHenrik Boström, Peter Höglund, Sven-Olof Junker, Ann-Sofie Öberg, Martin Sparr. [doi]

Towards Participatory Design Spaces for Explainable AI Interfaces in Expert Domains (Short Paper)Henrik Mucha, Sebastian Robert, Rüdiger Breitschwerdt, Michael Fellmann. [doi]

How to Teach a Computer to Learn About Microbes: KG-COVID-19 and Microbial Graph Learning - AbstractMarcin P. Joachimiak. [doi]

Foundations for Solving Classification Problems with Quantitative Abstract ArgumentationNico Potyka. [doi]

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