Maxim Panov

513 total citations
18 papers, 170 citations indexed

About

Maxim Panov is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Statistics and Probability. According to data from OpenAlex, Maxim Panov has authored 18 papers receiving a total of 170 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 5 papers in Statistical and Nonlinear Physics and 3 papers in Statistics and Probability. Recurrent topics in Maxim Panov's work include Complex Network Analysis Techniques (4 papers), Machine Learning and Algorithms (3 papers) and Topic Modeling (3 papers). Maxim Panov is often cited by papers focused on Complex Network Analysis Techniques (4 papers), Machine Learning and Algorithms (3 papers) and Topic Modeling (3 papers). Maxim Panov collaborates with scholars based in Russia, Germany and United Arab Emirates. Maxim Panov's co-authors include Yury Yanovich, Vladimir Spokoiny, Evgeny Burnaev, Alexey Zaytsev, Artem Shelmanov, Nikolai V. Brilliantov, Alexander Panchenko, Evgenii Tsymbalov, Svetlana A. Shabalina and Aleksey Y. Ogurtsov and has published in prestigious journals such as Nucleic Acids Research, Scientific Reports and International Journal of Hydrogen Energy.

In The Last Decade

Maxim Panov

17 papers receiving 163 citations

Peers

Maxim Panov

CVPR

CNC

SPS

Guolei Yang United States

Karim Tabia France

Hiroaki Ohshima Japan

Massih-Reza Amini France

Pengzhou Zhang China

Mourad Khayati Switzerland

Galina Bogdanova Bulgaria

Chengfang Fang Singapore

Guolei Yang United States

Maxim Panov

127 ×1.6

60 ×0.9

28 ×1.0

CVPR

26 ×1.1

CNC

8 ×0.5

SPS

Citations per year, relative to Maxim Panov Maxim Panov (= 1×) peers Guolei Yang

Countries citing papers authored by Maxim Panov

Since Specialization

Citations

This map shows the geographic impact of Maxim Panov'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 Maxim Panov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxim Panov more than expected).

Fields of papers citing papers by Maxim Panov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maxim Panov. 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 Maxim Panov. The network helps show where Maxim Panov may publish in the future.

Co-authorship network of co-authors of Maxim Panov

This figure shows the co-authorship network connecting the top 25 collaborators of Maxim Panov. A scholar is included among the top collaborators of Maxim Panov 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 Maxim Panov. Maxim Panov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Spokoiny, Vladimir & Maxim Panov. (2025). Accuracy of Gaussian approximation for high-dimensional posterior distributions. Bernoulli. 31(2). 1 indexed citations

Panchenko, Alexander, et al.. (2025). Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph. Transactions of the Association for Computational Linguistics. 13. 220–248. 1 indexed citations

Shelmanov, Artem, et al.. (2023). Uncertainty Estimation for Debiased Models: Does Fairness Hurt Reliability?. 744–770. 2 indexed citations

Panov, Maxim, et al.. (2023). Assigning topics to documents by successive projections. The Annals of Statistics. 51(5). 3 indexed citations

Panov, Maxim, et al.. (2022). Measuring internal inequality in capsule networks for supervised anomaly detection. Scientific Reports. 12(1). 13575–13575. 1 indexed citations

Savitskaya, Ekaterina, Maxim Panov, Aleksey Y. Ogurtsov, et al.. (2021). Uncertainty-aware and interpretable evaluation of Cas9–gRNA and Cas12a–gRNA specificity for fully matched and partially mismatched targets with Deep Kernel Learning. Nucleic Acids Research. 50(2). e11–e11. 11 indexed citations

Panov, Maxim, et al.. (2021). Why animals swirl and how they group. Scientific Reports. 11(1). 20843–20843. 10 indexed citations

Shelmanov, Artem, et al.. (2021). How Certain is Your Transformer?. 1833–1840. 16 indexed citations

Panov, Maxim, et al.. (2021). Inductive Matrix Completion with Feature Selection. Computational Mathematics and Mathematical Physics. 61(5). 719–732. 3 indexed citations

10.

Tsymbalov, Evgenii, et al.. (2020). Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampled Implicit Ensembles.. 1 indexed citations

11.

Panov, Maxim, et al.. (2020). Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data: Extended Abstract. 787–788. 2 indexed citations

12.

Fedorov, Fedor S., Maxim Panov, Alexander Rashkovskiy, et al.. (2019). Tailoring electrochemical efficiency of hydrogen evolution by fine tuning of TiOx/RuOx composite cathode architecture. International Journal of Hydrogen Energy. 44(21). 10593–10603. 5 indexed citations

13.

Panov, Maxim, et al.. (2019). Data-Driven Body-Machine Interface for Drone Intuitive Control through Voice and Gestures. 5602–5609. 14 indexed citations

14.

Panov, Maxim, et al.. (2017). Consistent parameter estimation in general stochastic block models with overlaps. arXiv (Cornell University).

15.

Panov, Maxim, et al.. (2017). Automatic Bitcoin Address Clustering. 461–466. 69 indexed citations

16.

Burnaev, Evgeny, Maxim Panov, & Alexey Zaytsev. (2016). Regression on the basis of nonstationary Gaussian processes with Bayesian regularization. Journal of Communications Technology and Electronics. 61(6). 661–671. 15 indexed citations

17.

Panov, Maxim & Vladimir Spokoiny. (2015). Finite Sample Bernstein – von Mises Theorem for Semiparametric Problems. Bayesian Analysis. 10(3). 14 indexed citations

18.

Panov, Maxim & Vladimir Spokoiny. (2014). Critical dimension in the semiparametric Bernstein—von Mises theorem. Proceedings of the Steklov Institute of Mathematics. 287(1). 232–255. 2 indexed citations

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.

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