David T. Frazier

100 total papers · 583 total citations
30 papers, 225 citations indexed

About

David T. Frazier is a scholar working on Statistics and Probability, Artificial Intelligence and Finance. According to data from OpenAlex, David T. Frazier has authored 30 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Statistics and Probability, 14 papers in Artificial Intelligence and 7 papers in Finance. Recurrent topics in David T. Frazier's work include Markov Chains and Monte Carlo Methods (11 papers), Statistical Methods and Bayesian Inference (10 papers) and Gaussian Processes and Bayesian Inference (8 papers). David T. Frazier is often cited by papers focused on Markov Chains and Monte Carlo Methods (11 papers), Statistical Methods and Bayesian Inference (10 papers) and Gaussian Processes and Bayesian Inference (8 papers). David T. Frazier collaborates with scholars based in Australia, Singapore and United Kingdom. David T. Frazier's co-authors include Christopher Drovandi, Christian P. Robert, Gael M. Martin, Judith Rousseau, Éric Renault, David J. Nott, Robert Kohn, Brendan McCabe, Scott A. Sisson and Bonsoo Koo and has published in prestigious journals such as Journal of the American Statistical Association, Journal of Econometrics and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

David T. Frazier

25 papers receiving 215 citations

Author Peers

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

Author						Papers	Cites
David T. Frazier	106	86	41	41	26	30	225
Masayuki Hirukawa	124 1.2×	50 0.6×	35 0.9×	126 3.1×	20 0.8×	22	325
Karine Bertin	154 1.5×	75 0.9×	54 1.3×	15 0.4×	22 0.8×	18	220
Daniela Jarušková	109 1.0×	31 0.4×	78 1.9×	16 0.4×	51 2.0×	30	312
Dario Gasbarra	112 1.1×	54 0.6×	29 0.7×	26 0.6×	19 0.7×	34	323
Martin Wendler	108 1.0×	34 0.4×	86 2.1×	59 1.4×	18 0.7×	28	249
Xiaoqian Sun	215 2.0×	63 0.7×	21 0.5×	78 1.9×	37 1.4×	27	315
Somesh Das Gupta	165 1.6×	47 0.5×	25 0.6×	29 0.7×	28 1.1×	24	293
Ching‐Kang Ing	137 1.3×	44 0.5×	58 1.4×	30 0.7×	25 1.0×	26	257
Luisa Turrin Fernholz	230 2.2×	57 0.7×	39 1.0×	20 0.5×	64 2.5×	18	312
Isabel Pereira	179 1.7×	66 0.8×	175 4.3×	28 0.7×	34 1.3×	21	277

Countries citing papers authored by David T. Frazier

Since Specialization

Citations

This map shows the geographic impact of David T. Frazier'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 David T. Frazier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Frazier more than expected).

Fields of papers citing papers by David T. Frazier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David T. Frazier. 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 David T. Frazier. The network helps show where David T. Frazier may publish in the future.

Co-authorship network of co-authors of David T. Frazier

This figure shows the co-authorship network connecting the top 25 collaborators of David T. Frazier. A scholar is included among the top collaborators of David T. Frazier 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 David T. Frazier. David T. Frazier 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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