Seiya Tokui

12 total papers · 830 total citations
2 papers, 70 citations indexed

About

Seiya Tokui is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Seiya Tokui has authored 2 papers receiving a total of 70 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Computer Vision and Pattern Recognition, 1 paper in Artificial Intelligence and 1 paper in Statistics and Probability. Recurrent topics in Seiya Tokui's work include Gaussian Processes and Bayesian Inference (1 paper), Stochastic Gradient Optimization Techniques (1 paper) and Advanced Image and Video Retrieval Techniques (1 paper). Seiya Tokui is often cited by papers focused on Gaussian Processes and Bayesian Inference (1 paper), Stochastic Gradient Optimization Techniques (1 paper) and Advanced Image and Video Retrieval Techniques (1 paper). Seiya Tokui collaborates with scholars based in Japan. Seiya Tokui's co-authors include Takuya Akiba, Toru Ogawa, Shunta Saito, Brian Vogel, Shuji Suzuki and Issei Sato and has published in prestigious journals such as International Conference on Machine Learning.

In The Last Decade

Seiya Tokui

2 papers receiving 69 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Seiya Tokui	33	30	10	6	6	2	70
Zachary Nado	75 2.3×	33 1.1×	7 0.7×	3 0.5×	3 0.5×	3	103
Chenggang Zhao	37 1.1×	54 1.8×	8 0.8×	12 2.0×	3 0.5×	5	110
Liam Li	65 2.0×	30 1.0×	6 0.6×	10 1.7×	2 0.3×	3	127
Wangding Zeng	21 0.6×	21 0.7×	5 0.5×	6 1.0×	2 0.3×	3	66
Satish Nadathur	34 1.0×	34 1.1×	18 1.8×	11 1.8×	17 2.8×	3	69
Ruikun Li	29 0.9×	13 0.4×	5 0.5×	6 1.0×		4	61
Aohan Zeng	46 1.4×	13 0.4×	5 0.5×	7 1.2×	3 0.5×	6	71
Steve Babbage	55 1.7×	31 1.0×	5 0.5×	6 1.0×	11 1.8×	3	60
Michael R. Zhang	32 1.0×	30 1.0×	4 0.4×	3 0.5×		3	72
Joseph Hassoun	30 0.9×	31 1.0×	6 0.6×	4 0.7×	5 0.8×	4	55

Countries citing papers authored by Seiya Tokui

Since Specialization

Citations

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

Fields of papers citing papers by Seiya Tokui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seiya Tokui

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

All Works

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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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