Elizaveta Levina
- Statistics and Probability top 0.1%
- Artificial Intelligence top 0.5%
- Molecular Biology top 10%
- Statistical and Nonlinear Physics top 1%
- Computer Vision and Pattern Recognition top 2%
- Co-authors
- Peter J. BickelJi ZhuAdam RothmanGeorge MichailidisM. E. J. NewmanBrian KarrerJuan GuoTianxi Li
- Topics
- Complex Network Analysis Techniques (19 papers)Statistical Methods and Inference (13 papers)Bayesian Methods and Mixture Models (10 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationTechnometrics
- Partner nations
- United StatesRussiaBelgium
In The Last Decade
Elizaveta Levina
49 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Statistics and Probability 1.8k
- Artificial Intelligence 1.4k
- Molecular Biology 702
- Statistical and Nonlinear Physics 684
- Computer Vision and Pattern Recognition 621
Countries citing papers authored by Elizaveta Levina
This map shows the geographic impact of Elizaveta Levina'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 Elizaveta Levina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Elizaveta Levina more than expected).
Fields of papers citing papers by Elizaveta Levina
This network shows the impact of papers produced by Elizaveta Levina. 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 Elizaveta Levina. The network helps show where Elizaveta Levina may publish in the future.
Co-authorship network of co-authors of Elizaveta Levina
This figure shows the co-authorship network connecting the top 25 collaborators of Elizaveta Levina. A scholar is included among the top collaborators of Elizaveta Levina 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 Elizaveta Levina. Elizaveta Levina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | High-dimensional Gaussian graphical models on network-linked data | 8 |
| 4 | 40 | |
| 5 | 46 | |
| 6 | 33 | |
| 7 | Optimization via Low-rank Approximation, with Applications to Community Detection in Networks. | 1 |
| 8 | 28 | |
| 9 | 39 | |
| 10 | Fitting community models to large sparse networks | 10 |
| 11 | The method of moments and degree distributions for network models | 90 |
| 12 | On Consistency of Community Detection in Networks | 4 |
| 13 | 215 | |
| 14 | 41 | |
| 15 | 44 | |
| 16 | 223 | |
| 17 | Regularized estimation of large covariance matricesbreakdown → | 730 |
| 18 | Covariance regularization by thresholdingbreakdown → | 689 |
| 19 | 9 | |
| 20 | Maximum Likelihood Estimation of Intrinsic Dimension | 399 |
About Elizaveta Levina
Elizaveta Levina is a scholar working on Statistics and Probability, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 53 papers that have together received 4.6k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (19 papers), Statistical Methods and Inference (13 papers) and Bayesian Methods and Mixture Models (10 papers). The work is most often cited by research in Statistics and Probability (1.8k citations), Computational Mathematics (36 citations) and Statistical and Nonlinear Physics (684 citations). Elizaveta Levina has collaborated with scholars based in United States, Russia and Belgium. Frequent co-authors include Peter J. Bickel, Ji Zhu, Adam Rothman, George Michailidis, M. E. J. Newman, Brian Karrer, Juan Guo, Tianxi Li, Yuan Zhang and Ji Zhu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and Technometrics.
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.