Xenia Miscouridou
- Artificial Intelligence
- Statistics and Probability
- Computational Mechanics
- Statistical and Nonlinear Physics
- Modeling and Simulation
- Co-authors
- Georgios C. GeorgiouRimma PerotteNoémie ElhadadFrançois CaronRajesh RanganathMikko S. PakkanenSwapnil MishraJuho Lee
- Topics
- Complex Network Analysis Techniques (2 papers)Statistical Methods and Inference (2 papers)Bayesian Methods and Mixture Models (2 papers)
- Partner nations
- United KingdomCyprusDenmark
In The Last Decade
Xenia Miscouridou
7 papers receiving 39 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 17
- Statistics and Probability 13
- Computational Mechanics 10
- Statistical and Nonlinear Physics 7
- Modeling and Simulation 7
Countries citing papers authored by Xenia Miscouridou
This map shows the geographic impact of Xenia Miscouridou'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 Xenia Miscouridou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xenia Miscouridou more than expected).
Fields of papers citing papers by Xenia Miscouridou
This network shows the impact of papers produced by Xenia Miscouridou. 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 Xenia Miscouridou. The network helps show where Xenia Miscouridou may publish in the future.
Co-authorship network of co-authors of Xenia Miscouridou
This figure shows the co-authorship network connecting the top 25 collaborators of Xenia Miscouridou. A scholar is included among the top collaborators of Xenia Miscouridou 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 Xenia Miscouridou. Xenia Miscouridou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting | 3 |
| 4 | Exchangeable random measures for sparse and modular graphs with overlapping communities | 12 |
| 5 | Deep Survival Analysis: Nonparametrics and Missingness. | 6 |
| 6 | Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data | 3 |
| 7 | 11 |
About Xenia Miscouridou
Xenia Miscouridou is a scholar working on Statistics and Probability, Modeling and Simulation and Fluid Flow and Transfer Processes, having authored 7 papers that have together received 42 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (2 papers), Statistical Methods and Inference (2 papers) and Bayesian Methods and Mixture Models (2 papers). The work is most often cited by research in Statistics and Probability (13 citations), Modeling and Simulation (7 citations) and Fluid Flow and Transfer Processes (5 citations). Xenia Miscouridou has collaborated with scholars based in United Kingdom, Cyprus and Denmark. Frequent co-authors include Georgios C. Georgiou, Rimma Perotte, Noémie Elhadad, François Caron, Rajesh Ranganath, Mikko S. Pakkanen, Swapnil Mishra, Juho Lee, Matthew J. Penn and Tresnia Berah. Their work appears in journals such as Journal of Mathematical Biology, Meccanica and Bernoulli.
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.