Olivér Kiss

689 citations
3 papers · 231 indexed · 1 hit paper · h-index 3
Topics
Complex Network Analysis Techniques (2 papers)Advanced Graph Neural Networks (2 papers)Imbalanced Data Classification Techniques (1 paper)
Journals
Edinburgh Research Explorer (University of Edinburgh)Edinburgh Research ExplorerProceedings of the Thirty-First International Joint Conference on Artificial Intelligence

In The Last Decade

Olivér Kiss

3 papers receiving 226 citations

Hit Papers

The Shapley Value in Machine Learning202220262023202420224080120

Peers

Olivér Kiss
Comparison fields: 5 of 90
  • Artificial Intelligence 120
  • Statistical and Nonlinear Physics 47
  • Computer Vision and Pattern Recognition 30
  • Information Systems 24
  • Molecular Biology 20
Replace Ziyue Qiao with:
Ziyue Qiao China
Amauri H. Souza Brazil
João Roberto Bertini Brazil
Pavel Kordík Czechia
Vincent Cohen-Addad United States
Ru Wang China
Ru Li China
Bingjun Sun United States
Olivér Kiss relative to Ziyue Qiao China Ziyue Qiao's profile →
Citations per field
00.5×2.9×
Ziyue Qiao · 1×
Citations per year

Countries citing papers authored by Olivér Kiss

Since Specialization
Citations

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

Fields of papers citing papers by Olivér Kiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivér Kiss

This figure shows the co-authorship network connecting the top 25 collaborators of Olivér Kiss. A scholar is included among the top collaborators of Olivér Kiss 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 Olivér Kiss. Olivér Kiss is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

3 of 3 papers shown
#WorkIndexed citations
1
The Shapley Value in Machine Learningbreakdown →
134
2 22
3 75

About Olivér Kiss

Olivér Kiss is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Molecular Biology, having authored 3 papers that have together received 231 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (2 papers), Advanced Graph Neural Networks (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (47 citations), Artificial Intelligence (120 citations) and Signal Processing (18 citations). Olivér Kiss has collaborated with scholars based in United Kingdom, Austria and Brazil. Frequent co-authors include Benedek Rózemberczki, Rik Sarkar, Hao-Tsung Yang and Péter Bayer. Their work appears in journals such as Edinburgh Research Explorer (University of Edinburgh), Edinburgh Research Explorer and Proceedings of the Thirty-First International Joint Conference on 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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