Michael Fink

69 papers receiving 1.1k citations

Peers

Michael Fink
Comparison fields: 5 of 99
  • Artificial Intelligence 834
  • Computer Vision and Pattern Recognition 348
  • Computer Networks and Communications 135
  • Signal Processing 117
  • Computational Mechanics 116
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Countries citing papers authored by Michael Fink

Since Specialization
Citations

This map shows the geographic impact of Michael Fink'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 Michael Fink with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Fink more than expected).

Fields of papers citing papers by Michael Fink

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Fink. 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 Michael Fink. The network helps show where Michael Fink may publish in the future.

Co-authorship network of co-authors of Michael Fink

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Fink. A scholar is included among the top collaborators of Michael Fink based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Fink. Michael Fink is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 17
2 12
3 27
4
Towards Practical Deletion Repair of Inconsistent DL-programs.
2
5
Data repair of inconsistent DL-programs
3
6
Paraconsistent hybrid theories
7
7
Distributed nonmonotonic multi-context systems
12
8
Finding explanations of inconsistency in multi-context systems
11
9
Decomposition of declarative knowledge bases with external functions
3
10
Online Learning of Search Heuristics
10
11
Complexity results for checking equivalence of stratified logic programs
8
12
Resolving Conflicts in Action Descriptions
4
13
Updating action domain descriptions
14
14
Strong and uniform equivalence in answer-set programming: characterizations and complexity results for the non-ground case
19
15
Complexity of model checking and bounded predicate arities for non-ground answer set programming
7
16
Object Classification from a Single Example Utilizing Class Relevance Metrics
119
17
On eliminating disjunctions in stable logic programming
10
18
Mutual Boosting for Contextual Inference
66
19
A generic approach for knowledge-based information-site selection
6
20 18

About Michael Fink

Michael Fink is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 71 papers that have together received 1.2k indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (46 papers), Multi-Agent Systems and Negotiation (29 papers) and Semantic Web and Ontologies (25 papers). The work is most often cited by research in Artificial Intelligence (834 citations), Computer Vision and Pattern Recognition (348 citations) and Computational Mathematics (7 citations). Michael Fink has collaborated with scholars based in Austria, Israel and United States. Frequent co-authors include Thomas Eiter, Shimon Ullman, Nathan Srebro, Pietro Perona, Stefan Woltran, Hans Tompits, Thomas Krennwallner, Peter Schüller, Christoph Redl and Shumeet Baluja. Their work appears in journals such as Monthly Notices of the Royal Astronomical Society, International Journal of Computer Vision and Artificial 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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