Sergios Agapiou
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Markov Chains and Monte Carlo Methods
- Statistical Methods and Bayesian Inference
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- Probabilistic and Robust Engineering Design
Papers in
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- Gaussian Processes and Bayesian Inference 6
- Bayesian Methods and Mixture Models 2
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- Statistical Methods and Inference 4
- Markov Chains and Monte Carlo Methods 3
- Co-authors
- Andrew M. Stuart (5 shared papers)Omiros Papaspiliopoulos (2 shared papers)Daniel Sanz-Alonso (1 shared paper)Stig Larsson (2 shared papers)Johnathan M. Bardsley (1 shared paper)Martin Burger (1 shared paper)Yuanxiang Zhang (1 shared paper)Masoumeh Dashti (1 shared paper)
- Journals
- Stochastic Processes and their Applications (1 paper)Bernoulli (1 paper)Electronic Journal of Statistics (1 paper)Inverse Problems (1 paper)SIAM/ASA Journal on Uncertainty Quantification (1 paper)
- Partner nations
- CyprusUnited KingdomUnited States
In The Last Decade
Sergios Agapiou
10 papers receiving 183 citations
Peers
Comparison fields: 5 of 44
- Statistics and Probability 99
- Statistics, Probability and Uncertainty 59
- Mathematical Physics 50
- Artificial Intelligence 96
- Applied Mathematics 11
Countries citing papers authored by Sergios Agapiou
This map shows the geographic impact of Sergios Agapiou'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 Sergios Agapiou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergios Agapiou more than expected).
Fields of papers citing papers by Sergios Agapiou
This network shows the impact of papers produced by Sergios Agapiou. 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 Sergios Agapiou. The network helps show where Sergios Agapiou may publish in the future.
Co-authors
The 17 scholars most cited alongside Sergios Agapiou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 76 | |
| 2 | 2013 | 43 | |
| 3 | 2014 | 26 | |
| 4 | 2018 | 18 | |
| 5 | 2013 | 16 | |
| 6 | POSTERIOR CONSISTENCY OF THE BAYESIAN APPROACH TO LINEAR ILL-POSED INVERSE PROBLEMS | 2012 | 9 |
| 7 | 2021 | 4 | |
| 8 | 2022 | 4 | |
| 9 | 2024 | 1 | |
| 10 | 2024 | 1 |
About Sergios Agapiou
Sergios Agapiou is a scholar working on Artificial Intelligence, Statistics and Probability, Mathematical Physics, Statistics, Probability and Uncertainty and Computer Vision and Pattern Recognition, having authored 10 papers that have together received 198 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (6 papers), Statistical Methods and Inference (4 papers), Markov Chains and Monte Carlo Methods (3 papers), Probabilistic and Robust Engineering Design (3 papers), Numerical methods in inverse problems (3 papers), Bayesian Methods and Mixture Models (2 papers), Agricultural risk and resilience (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Statistics and Probability (99 citations), Statistics, Probability and Uncertainty (59 citations), Mathematical Physics (50 citations), Artificial Intelligence (96 citations) and Applied Mathematics (11 citations). Sergios Agapiou has collaborated with scholars based in Cyprus, United Kingdom and United States. Frequent co-authors include Andrew M. Stuart, Omiros Papaspiliopoulos, Daniel Sanz-Alonso, Stig Larsson, Johnathan M. Bardsley, Martin Burger, Yuanxiang Zhang, Masoumeh Dashti, Tapio Helin and Peter Mathé. Their work appears in journals such as Stochastic Processes and their Applications, Bernoulli, Electronic Journal of Statistics, Inverse Problems and SIAM/ASA Journal on Uncertainty Quantification.
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.