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个人简介
Research interests of Ute Schmid are mainly in the domain of comprehensible machine learning, explainable AI, and high-level learning on relational data, especially inductive programming. Research topics are generation of visual, verbal and example-based explanations, cognitive tutor systems, cooperative and interactive learning, knowledge level learning from planning, learning structural prototypes, analogical problem solving and learning. Further research is on various applications of machine learning (e.g., classifier learning from medical data and for facial expressions) and empirical and experimental work on high-level cognitive processes. Ute Schmid is a pioneer of Computer Science for Primary School (FELI) and is engaged in the domain of AI education.
研究兴趣
论文共 296 篇作者统计合作学者相似作者
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arxiv(2024)
Michael Kohlhase,Marc Berges, Jens Grubert,Andreas Henrich,Dieter Landes,Jochen L. Leidner,Florian Mittag,Daniela Nicklas,Ute Schmid, Yvonne Sedlmaier, Achim Ulbrich-vom Ende,Diedrich Wolter
KI Künstliche Intelligenz/KI - Künstliche Intelligenz (2024)
CoRR (2024)
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Data Mining and Knowledge Discoverypp.1-25, (2024)
Lecture Notes in Computer Science KI 2024 Advances in Artificial Intelligencepp.324-331, (2024)
EXPLAINABLE ARTIFICIAL INTELLIGENCE, PT I, XAI 2024 (2024): 137-159
CoRR (2024)
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ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, PT I, AIAI 2024 (2024): 105-116
CoRR (2024)
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作者统计
#Papers: 296
#Citation: 3441
H-Index: 26
G-Index: 39
Sociability: 6
Diversity: 0
Activity: 4
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