Jake Grigsby

20 total papers · 712 total citations
2 papers, 306 citations indexed

About

Jake Grigsby is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Jake Grigsby has authored 2 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Signal Processing. Recurrent topics in Jake Grigsby's work include Generative Adversarial Networks and Image Synthesis (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and Adversarial Robustness in Machine Learning (1 paper). Jake Grigsby is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (1 paper), Domain Adaptation and Few-Shot Learning (1 paper) and Adversarial Robustness in Machine Learning (1 paper). Jake Grigsby collaborates with scholars based in United States. Jake Grigsby's co-authors include Yanjun Qi, Di Jin, John X. Morris, Eli Lifland, Jin Yong Yoo, Simonetta Liuti, Matthias Burkardt, L. P. Alonzi and J. R. Hoskins and has published in prestigious journals such as Physical review. D.

In The Last Decade

Jake Grigsby

2 papers receiving 295 citations

Hit Papers

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Author Peers

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

Author Last Decade Papers Cites
Jake Grigsby 266 65 36 33 26 2 306
Jin Yong Yoo 322 1.2× 81 1.2× 46 1.3× 40 1.2× 34 1.3× 6 358
Ahoud Alhazmi 246 0.9× 67 1.0× 48 1.3× 42 1.3× 21 0.8× 8 292
Shike Mei 201 0.8× 50 0.8× 28 0.8× 22 0.7× 15 0.6× 6 273
Kay Cohen 244 0.9× 56 0.9× 30 0.8× 37 1.1× 9 0.3× 4 330
Ammar Ismael Kadhim 253 1.0× 19 0.3× 125 3.5× 25 0.8× 28 1.1× 8 350
Yeganeh Kordi 186 0.7× 11 0.2× 38 1.1× 41 1.2× 6 0.2× 2 259
Shurui Gui 222 0.8× 27 0.4× 35 1.0× 72 2.2× 5 0.2× 3 349
Mojtaba Heidarysafa 222 0.8× 14 0.2× 59 1.6× 27 0.8× 6 0.2× 3 314
Xi Chen 182 0.7× 27 0.4× 53 1.5× 47 1.4× 16 0.6× 5 323
Arjun Narayan 262 1.0× 66 1.0× 99 2.8× 8 0.2× 34 1.3× 10 361

Countries citing papers authored by Jake Grigsby

Since Specialization
Citations

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

Fields of papers citing papers by Jake Grigsby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jake Grigsby

This figure shows the co-authorship network connecting the top 25 collaborators of Jake Grigsby. A scholar is included among the top collaborators of Jake Grigsby 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 Jake Grigsby. Jake Grigsby 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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