Ute Schmid

2.3k citations
104 papers · 916 · h-index 17

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Explainable Artificial Intelligence (XAI)
    • AI-based Problem Solving and Planning
    • Logic, Reasoning, and Knowledge
    • Machine Learning in Healthcare
    • Machine Learning and Algorithms

Papers in

    • Explainable Artificial Intelligence (XAI) 18
    • AI-based Problem Solving and Planning 12
    • Machine Learning and Algorithms 9
    • Semantic Web and Ontologies 8
    • Machine Learning and Data Classification 7
    • Logic, programming, and type systems 6
    • Computability, Logic, AI Algorithms 11

Ute Schmid

93 papers receiving 849 citations

Peers

Ute Schmid
Comparison fields: 5 of 125
  • Health Informatics 51
  • Artificial Intelligence 496
  • Software 45
  • Information Systems and Management 61
  • Computer Science Applications 40
Replace Xiaoyuan Yi with:
Xiaoyuan Yi China
Alexander Koller Germany
Kartik Talamadupula United States
Emily Reif United States
Antonios Liapis Malta
James Eagan United States
Artur d’Avila Garcez United Kingdom
Jian Zhao Canada
Toyoaki Nishida Japan
Ilana Heintz United States
Ute Schmid relative to Xiaoyuan Yi China Xiaoyuan Yi's profile →
Citations per field
00.5×1.5×2.0×
Xiaoyuan Yi · 1×
Citations per year

Countries citing papers authored by Ute Schmid

Since Specialization
Citations

This map shows the geographic impact of Ute Schmid's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ute Schmid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ute Schmid more than expected).

Fields of papers citing papers by Ute Schmid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ute Schmid. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ute Schmid. The network helps show where Ute Schmid may publish in the future.

Co-authors

The 25 scholars most cited alongside Ute Schmid, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ute Schmid Line = papers co-authored together Ute Schmid links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201571
2 202065
3 201856
4 202043
5
Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach
200640
6 201537
7 200532
8 201931
9 202327
10 201027
11 202026
12 201025
13 202423
14 202123
15 200818
16
Inductive Synthesis of Functional Programs: Universal Planning, Folding of Finite Programs, and Schema Abstraction by Analogical Reasoning
200318
17 202117
18 202216
19 201514
20 202314

About Ute Schmid

Ute Schmid is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Information Systems, having authored 104 papers that have together received 916 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (18 papers), AI-based Problem Solving and Planning (12 papers), Computability, Logic, AI Algorithms (11 papers), Machine Learning and Algorithms (9 papers), Teaching and Learning Programming (9 papers), Semantic Web and Ontologies (8 papers), Machine Learning and Data Classification (7 papers) and Logic, programming, and type systems (6 papers). The work is most often cited by research in Health Informatics (51 citations), Artificial Intelligence (496 citations), Software (45 citations), Information Systems and Management (61 citations) and Computer Science Applications (40 citations). Ute Schmid has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Emanuel Kitzelmann, Bettina Finzel, Stephen Muggleton, José Hernández‐Orallo, Michael Siebers, Katharina Weitz, Jens-Uwe Garbas, Teena Hassan, Tarek R. Besold and Helmar Gust. Their work appears in journals such as Cognitive Systems Research, Machine Learning, IEEE Transactions on Visualization and Computer Graphics, KI - Künstliche Intelligenz and Applied Intelligence.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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