Satoshi Kuriki
- Statistics and Probability top 2%
- Artificial Intelligence
- Applied Mathematics top 5%
- Electrical and Electronic Engineering
- Genetics
- Co-authors
- Akimichi TakemuraAnthony J. HayterTetsuhisa MiwaGwo Dong LinSteven D. BlosteinChihiro HirotsuYoshikazu MiyanagaHyundong Shin
- Topics
- Bayesian Methods and Mixture Models (12 papers)Statistical Methods and Bayesian Inference (11 papers)Point processes and geometric inequalities (10 papers)
- Journals
- GeneticsBiometrikaJournal of the Royal Statistical Society Series B (Statistical Methodology)
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Satoshi Kuriki
50 papers receiving 514 citations
Peers
Comparison fields: 5 of 94
- Statistics and Probability 222
- Artificial Intelligence 84
- Applied Mathematics 80
- Electrical and Electronic Engineering 74
- Genetics 73
Countries citing papers authored by Satoshi Kuriki
This map shows the geographic impact of Satoshi Kuriki'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 Satoshi Kuriki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satoshi Kuriki more than expected).
Fields of papers citing papers by Satoshi Kuriki
This network shows the impact of papers produced by Satoshi Kuriki. 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 Satoshi Kuriki. The network helps show where Satoshi Kuriki may publish in the future.
Co-authorship network of co-authors of Satoshi Kuriki
This figure shows the co-authorship network connecting the top 25 collaborators of Satoshi Kuriki. A scholar is included among the top collaborators of Satoshi Kuriki 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 Satoshi Kuriki. Satoshi Kuriki 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 | 0 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | 12 | |
| 6 | 5 | |
| 7 | EM algorithms for estimating the Bernstein copula function | 2 |
| 8 | 6 | |
| 9 | 5 | |
| 10 | 13 | |
| 11 | 2 | |
| 12 | 11 | |
| 13 | 12 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | 5 | |
| 17 | 1 | |
| 18 | Maximum Covariance Di erence Test for Equality of Two Covariance Matrices | 0 |
| 19 | 11 | |
| 20 | Weights of $\bar{x}^2$ distribution for smooth or piecewise smooth cone alternatives | 19 |
About Satoshi Kuriki
Satoshi Kuriki is a scholar working on Statistics and Probability, Computational Mathematics and Applied Mathematics, having authored 55 papers that have together received 539 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (12 papers), Statistical Methods and Bayesian Inference (11 papers) and Point processes and geometric inequalities (10 papers). The work is most often cited by research in Statistics and Probability (222 citations), Computational Mathematics (6 citations) and Applied Mathematics (80 citations). Satoshi Kuriki has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Akimichi Takemura, Anthony J. Hayter, Tetsuhisa Miwa, Gwo Dong Lin, Steven D. Blostein, Chihiro Hirotsu, Yoshikazu Miyanaga, Hyundong Shin, Kazuo Moriwaki and Toshihiko Shiroishi. Their work appears in journals such as Genetics, Biometrika and Journal of the Royal Statistical Society Series B (Statistical Methodology).
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.