Samuel Daulton

21 total papers · 660 total citations
2 papers, 113 citations indexed

About

Samuel Daulton is a scholar working on Artificial Intelligence, Management Science and Operations Research and Infectious Diseases. According to data from OpenAlex, Samuel Daulton has authored 2 papers receiving a total of 113 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Management Science and Operations Research and 0 papers in Infectious Diseases. Recurrent topics in Samuel Daulton's work include Advanced Bandit Algorithms Research (2 papers), Machine Learning and Algorithms (2 papers) and Machine Learning and Data Classification (2 papers). Samuel Daulton is often cited by papers focused on Advanced Bandit Algorithms Research (2 papers), Machine Learning and Algorithms (2 papers) and Machine Learning and Data Classification (2 papers). Samuel Daulton collaborates with scholars based in United States and Israel. Samuel Daulton's co-authors include Benjamin Letham, Brian Karrer, Maximilian Balandat, Andrew Gordon Wilson, Eytan Bakshy and Daniel Jiang and has published in prestigious journals such as arXiv (Cornell University).

In The Last Decade

Samuel Daulton

2 papers receiving 110 citations

Author Peers

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

Author Last Decade Papers Cites
Samuel Daulton 45 40 14 12 11 2 113
Ky Vu 34 0.8× 46 1.1× 23 1.6× 9 0.8× 13 1.2× 5 139
Yu. V. Prohorov 26 0.6× 15 0.4× 22 1.6× 5 0.4× 5 0.5× 7 218
Steven J. Leon 23 0.5× 29 0.7× 2 0.1× 6 0.5× 8 0.7× 5 116
Alexander I. Cowen-Rivers 31 0.7× 23 0.6× 4 0.3× 11 0.9× 3 0.3× 6 91
Łukasz Bartczuk 48 1.1× 20 0.5× 5 0.4× 4 0.3× 4 0.4× 3 109
R. D. Williams 17 0.4× 21 0.5× 12 0.9× 4 0.3× 5 0.5× 5 166
Liam Li 65 1.4× 10 0.3× 7 0.5× 2 0.2× 6 0.5× 3 127
J. K. Reid 12 0.3× 59 1.5× 4 0.3× 2 0.2× 5 0.5× 2 150
Payel Roy 41 0.9× 23 0.6× 6 0.4× 4 0.3× 7 0.6× 4 181
Jason Jo 76 1.7× 15 0.4× 8 0.6× 7 0.6× 4 0.4× 3 143

Countries citing papers authored by Samuel Daulton

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Daulton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Daulton

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