Mark Sellke
- Artificial Intelligence
- Condensed Matter Physics
- Statistics and Probability top 10%
- Computational Theory and Mathematics
- Mathematical Physics
- Co-authors
- A. El AlaouiAndrea MontanariAleksandrs SlivkinsYuval PeresGireeja RanadeVictoria KostinaSébastien BubeckYin Tat Lee
- Topics
- Theoretical and Computational Physics (10 papers)Markov Chains and Monte Carlo Methods (6 papers)Random Matrices and Applications (5 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignStatistics and ProbabilityCondensed Matter Physics
- Journals
- IEEE Transactions on Information TheoryOperations ResearchCommunications in Mathematical Physics
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Mark Sellke
22 papers receiving 136 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 42
- Condensed Matter Physics 35
- Statistics and Probability 26
- Computational Theory and Mathematics 22
- Mathematical Physics 20
Countries citing papers authored by Mark Sellke
This map shows the geographic impact of Mark Sellke'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 Mark Sellke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Sellke more than expected).
Fields of papers citing papers by Mark Sellke
This network shows the impact of papers produced by Mark Sellke. 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 Mark Sellke. The network helps show where Mark Sellke may publish in the future.
Co-authorship network of co-authors of Mark Sellke
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Sellke. A scholar is included among the top collaborators of Mark Sellke 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 Mark Sellke. Mark Sellke 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 | 1 | |
| 3 | 7 | |
| 4 | 0 | |
| 5 | 8 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 14 | |
| 11 | 9 | |
| 12 | 22 | |
| 13 | 0 | |
| 14 | 5 | |
| 15 | 12 | |
| 16 | Sample Complexity of Incentivized Exploration. | 1 |
| 17 | 9 | |
| 18 | 11 | |
| 19 | 5 | |
| 20 | 4 |
About Mark Sellke
Mark Sellke is a scholar working on Statistics and Probability, Condensed Matter Physics and Discrete Mathematics and Combinatorics, having authored 27 papers that have together received 138 indexed citations. Recurring topics across this work include Theoretical and Computational Physics (10 papers), Markov Chains and Monte Carlo Methods (6 papers) and Random Matrices and Applications (5 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (11 citations), Statistics and Probability (26 citations) and Condensed Matter Physics (35 citations). Mark Sellke has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include A. El Alaoui, Andrea Montanari, Aleksandrs Slivkins, Yuval Peres, Gireeja Ranade, Victoria Kostina, Sébastien Bubeck, Yin Tat Lee, Sitan Chen and Jerry Li. Their work appears in journals such as IEEE Transactions on Information Theory, Operations Research and Communications in Mathematical Physics.
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.