David A. van Dyk

5.9k total citations · 2 hit papers
82 papers, 3.5k citations indexed

About

David A. van Dyk is a scholar working on Statistics and Probability, Astronomy and Astrophysics and Artificial Intelligence. According to data from OpenAlex, David A. van Dyk has authored 82 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 29 papers in Astronomy and Astrophysics and 22 papers in Artificial Intelligence. Recurrent topics in David A. van Dyk's work include Statistical Methods and Bayesian Inference (20 papers), Gamma-ray bursts and supernovae (17 papers) and Stellar, planetary, and galactic studies (16 papers). David A. van Dyk is often cited by papers focused on Statistical Methods and Bayesian Inference (20 papers), Gamma-ray bursts and supernovae (17 papers) and Stellar, planetary, and galactic studies (16 papers). David A. van Dyk collaborates with scholars based in United States, United Kingdom and France. David A. van Dyk's co-authors include Xiao‐Li Meng, Kosuke Imai, Taeyoung Park, V. Kashyap, Aneta Siemiginowska, A. Connors, Rostislav S. Protassov, Ted von Hippel, Mark E. Glickman and W. H. Jefferys and has published in prestigious journals such as Journal of the American Statistical Association, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

David A. van Dyk

72 papers receiving 3.2k citations

Hit Papers

The Art of Data Augmentation 2001 2026 2009 2017 2001 2004 200 400 600

Peers

David A. van Dyk
Comparison fields: 5 of 187
  • Statistics and Probability 1.2k
  • Artificial Intelligence 937
  • Astronomy and Astrophysics 666
  • Economics and Econometrics 323
  • Nuclear and High Energy Physics 241
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Citations per field, relative to David A. van Dyk
David A. van Dyk · 1×
Citations per year, relative to David A. van Dyk
David A. van Dyk · 1×

Countries citing papers authored by David A. van Dyk

Since Specialization
Citations

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

Fields of papers citing papers by David A. van Dyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. van Dyk. 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 A. van Dyk. The network helps show where David A. van Dyk may publish in the future.

Co-authorship network of co-authors of David A. van Dyk

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 2
3 2
4 1
5 0
6 4
7 2
8 3
9 8
10 32
11
BASE-9: Bayesian Analysis for Stellar Evolution with nine variables
1
12 4
13 17
14 20
15
LIRA — The Low-Counts Image Restoration and Analysis Package: A Teaching Version via R
1
16
pyblocxs: Bayesian Low-Counts X-ray Spectral Analysis in Sherpa
1
17
Inverting Color-Magnitude Diagrams to Access Precise Star Cluster Parameters: A Bayesian Approach
1
18 48
19
A Fe K Line in GRB 970508
1
20 20

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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