Vladislav B. Tadić
- Artificial Intelligence top 2%
- Control and Systems Engineering top 5%
- Statistics and Probability top 5%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Co-authors
- Randal DoucChristophe AndrieuSumeetpal S. SinghSean MeynShane G. HendersonAdam M. JohansenSrdjan StankovićR. Porter
- Topics
- Target Tracking and Data Fusion in Sensor Networks (14 papers)Markov Chains and Monte Carlo Methods (11 papers)Control Systems and Identification (10 papers)
- Journals
- Proceedings of the IEEEIEEE Transactions on Information TheoryEuropean Journal of Operational Research
- Partner nations
- United KingdomAustraliaSerbia
In The Last Decade
Vladislav B. Tadić
42 papers receiving 730 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 484
- Control and Systems Engineering 287
- Statistics and Probability 109
- Computer Networks and Communications 108
- Electrical and Electronic Engineering 74
Countries citing papers authored by Vladislav B. Tadić
This map shows the geographic impact of Vladislav B. Tadić'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 Vladislav B. Tadić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vladislav B. Tadić more than expected).
Fields of papers citing papers by Vladislav B. Tadić
This network shows the impact of papers produced by Vladislav B. Tadić. 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 Vladislav B. Tadić. The network helps show where Vladislav B. Tadić may publish in the future.
Co-authorship network of co-authors of Vladislav B. Tadić
This figure shows the co-authorship network connecting the top 25 collaborators of Vladislav B. Tadić. A scholar is included among the top collaborators of Vladislav B. Tadić 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 Vladislav B. Tadić. Vladislav B. Tadić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | Blind separation of sources with finite rate of innovation | 3 |
| 6 | 8 | |
| 7 | 32 | |
| 8 | 55 | |
| 9 | 20 | |
| 10 | 227 | |
| 11 | 9 | |
| 12 | 5 | |
| 13 | 40 | |
| 14 | 147 | |
| 15 | 1 | |
| 16 | 5 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 5 |
About Vladislav B. Tadić
Vladislav B. Tadić is a scholar working on Statistics and Probability, Artificial Intelligence and Numerical Analysis, having authored 43 papers that have together received 784 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (14 papers), Markov Chains and Monte Carlo Methods (11 papers) and Control Systems and Identification (10 papers). The work is most often cited by research in Artificial Intelligence (484 citations), Statistics and Probability (109 citations) and Control and Systems Engineering (287 citations). Vladislav B. Tadić has collaborated with scholars based in United Kingdom, Australia and Serbia. Frequent co-authors include Randal Douc, Christophe Andrieu, Sumeetpal S. Singh, Sean Meyn, Shane G. Henderson, Adam M. Johansen, Srdjan Stanković, R. Porter, Alin Achim and Roberto Tempo. Their work appears in journals such as Proceedings of the IEEE, IEEE Transactions on Information Theory and European Journal of Operational 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.