Milan Studený
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 2%
- Management Science and Operations Research top 5%
- Signal Processing top 5%
- Statistics and Probability top 5%
- Co-authors
- Remco BouckaertFrancesco M. MalvestutoRaymond HemmeckeJiří VomlelDavid HawsFrantišek MatúšIan H. WittenJon Kleinberg
- Topics
- Bayesian Modeling and Causal Inference (33 papers)Rough Sets and Fuzzy Logic (11 papers)Multi-Criteria Decision Making (9 papers)
- Partner nations
- CzechiaUnited KingdomUnited States
In The Last Decade
Milan Studený
45 papers receiving 594 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 566
- Computational Theory and Mathematics 225
- Management Science and Operations Research 120
- Signal Processing 105
- Statistics and Probability 85
Countries citing papers authored by Milan Studený
This map shows the geographic impact of Milan Studený'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 Milan Studený with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Milan Studený more than expected).
Fields of papers citing papers by Milan Studený
This network shows the impact of papers produced by Milan Studený. 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 Milan Studený. The network helps show where Milan Studený may publish in the future.
Co-authorship network of co-authors of Milan Studený
This figure shows the co-authorship network connecting the top 25 collaborators of Milan Studený. A scholar is included among the top collaborators of Milan Studený 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 Milan Studený. Milan Studený is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Dual Formulation of the Chordal Graph Conjecture | 1 |
| 3 | 0 | |
| 4 | 3 | |
| 5 | Linear Core-Based Criterion for Testing Extreme Exact Games. | 1 |
| 6 | 7 | |
| 7 | How matroids occur in the context of learning Bayesian network structure | 1 |
| 8 | 26 | |
| 9 | 11 | |
| 10 | TWO OPERATIONS OF MERGING AND SPLITTING COMPONENTS IN A CHAIN GRAPH | 10 |
| 11 | 9 | |
| 12 | Comparison of two methods for approximation of probability distributions with prescribed marginals | 1 |
| 13 | A Graphical Representation of Equivalence Classes of AMP Chain Graphs | 15 |
| 14 | Probabilistic Conditional Independence Structures: With 42 Illustrations (Information Science and Statistics) | 28 |
| 15 | Characterization of Essential Graphs by Means of an Operation of Legal Component Merging. | 4 |
| 16 | Conditional products: An alternative approach to conditional independence | 7 |
| 17 | 30 | |
| 18 | Convex cones in finite-dimensional real vector spaces | 6 |
| 19 | 14 | |
| 20 | Asymptotic behaviour of empirical multiinformation | 3 |
About Milan Studený
Milan Studený is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research, having authored 52 papers that have together received 690 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (33 papers), Rough Sets and Fuzzy Logic (11 papers) and Multi-Criteria Decision Making (9 papers). The work is most often cited by research in Artificial Intelligence (566 citations), Computational Theory and Mathematics (225 citations) and Statistics and Probability (85 citations). Milan Studený has collaborated with scholars based in Czechia, United Kingdom and United States. Frequent co-authors include Remco Bouckaert, Francesco M. Malvestuto, Raymond Hemmecke, Jiří Vomlel, David Haws, František Matúš, Ian H. Witten, Jon Kleinberg, Alberto Roverato and Michael I. Jordan. Their work appears in journals such as The Annals of Statistics, Information Sciences and Journal of Machine Learning Research.
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.