Danila Sinopalnikov

1.1k total citations
3 papers, 28 citations indexed

About

Danila Sinopalnikov is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Infectious Diseases. According to data from OpenAlex, Danila Sinopalnikov has authored 3 papers receiving a total of 28 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 0 papers in Infectious Diseases. Recurrent topics in Danila Sinopalnikov's work include Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers) and Multimodal Machine Learning Applications (2 papers). Danila Sinopalnikov is often cited by papers focused on Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers) and Multimodal Machine Learning Applications (2 papers). Danila Sinopalnikov collaborates with scholars based in United States and United Kingdom. Danila Sinopalnikov's co-authors include Nikola Momchev, Dmitry Tsarkov, Nathanael Schärli, Nathan Scales, Sergii Kashubin, Hylke Buisman, Daniel Keysers, Marc van Zee, Olivier Bousquet and Xiao Wang and has published in prestigious journals such as arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Danila Sinopalnikov

2 papers receiving 26 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Danila Sinopalnikov United States	2	27	14	2	2	1	3	28
Karan Goel United States	4	21 0.8×	9 0.6×	3 1.5×	2 1.0×	1 1.0×	10	34
Nikola Momchev United States	3	36 1.3×	14 1.0×	2 1.0×	4 2.0×	1 1.0×	5	38
Ozan Çağlayan United Kingdom	3	32 1.2×	20 1.4×		2 1.0×	1 1.0×	4	41
Shreyas Saxena France	2	25 0.9×	9 0.6×		2 1.0×		3	29
Carolin Haas Germany	4	23 0.9×	10 0.7×		3 1.5×	1 1.0×	5	30
David Ha Japan	3	20 0.7×	10 0.7×	4 2.0×	3 1.5×		11	29
Didrik Nielsen Denmark	3	14 0.5×	15 1.1×	2 1.0×	1 0.5×		4	23
Chris Waites United States	3	23 0.9×	8 0.6×		2 1.0×	1 1.0×	4	24
Flood Sung United Kingdom	2	20 0.7×	13 0.9×				3	23
Nayan Singhal United States	3	22 0.8×	18 1.3×		1 0.5×		3	40

Countries citing papers authored by Danila Sinopalnikov

Since Specialization

Citations

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

Fields of papers citing papers by Danila Sinopalnikov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danila Sinopalnikov

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

All Works

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3 of 3 papers shown

1.

Tsarkov, Dmitry, et al.. (2021). *-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task. Proceedings of the AAAI Conference on Artificial Intelligence. 35(11). 9949–9957. 8 indexed citations

2.

Tsarkov, Dmitry, et al.. (2020). *-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task. arXiv (Cornell University). 35(11). 9949–9957.

3.

Keysers, Daniel, Nathanael Schärli, Nathan Scales, et al.. (2019). Measuring Compositional Generalization: A Comprehensive Method on Realistic Data. arXiv (Cornell University). 20 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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