Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Stan: A Probabilistic Programming Language
20174.3k citationsBob Carpenter, Andrew Gelman et al.Journal of Statistical Softwareprofile →
Visualization in Bayesian Workflow
2019604 citationsJonah Gabry, Daniel Simpson et al.Journal of the Royal Statistical Society Series A (Statistics in Society)profile →
Countries citing papers authored by Michael Betancourt
Since
Specialization
Citations
This map shows the geographic impact of Michael Betancourt'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 Michael Betancourt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Betancourt more than expected).
Fields of papers citing papers by Michael Betancourt
This network shows the impact of papers produced by Michael Betancourt. 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 Michael Betancourt. The network helps show where Michael Betancourt may publish in the future.
Co-authorship network of co-authors of Michael Betancourt
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Betancourt.
A scholar is included among the top collaborators of Michael Betancourt 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 Michael Betancourt. Michael Betancourt is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Schad, Daniel J., Bruno Nicenboim, Paul‐Christian Bürkner, Michael Betancourt, & Shravan Vasishth. (2022). Workflow techniques for the robust use of bayes factors.. Psychological Methods. 28(6). 1404–1426.56 indexed citations
Gabry, Jonah, Daniel Simpson, Aki Vehtari, Michael Betancourt, & Andrew Gelman. (2019). Visualization in Bayesian Workflow. Journal of the Royal Statistical Society Series A (Statistics in Society). 182(2). 389–402.604 indexed citations breakdown →
Carpenter, Bob, Andrew Gelman, Matthew D. Hoffman, et al.. (2017). Stan: A Probabilistic Programming Language. Journal of Statistical Software. 76(1).4257 indexed citations breakdown →
12.
Gelman, Andrew, Daniel Simpson, & Michael Betancourt. (2017). The Prior Can Often Only Be Understood in the Context of the Likelihood. Columbia Academic Commons (Columbia University).302 indexed citations breakdown →
Betancourt, Michael. (2015). The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling. International Conference on Machine Learning. 533–540.11 indexed citations
Balewski, J., Michael Betancourt, R. Corliss, et al.. (2012). Longitudinal and transverse spin asymmetries for inclusive jet production at mid-rapidity in polarized p+p collisions at √s=200 GeV. DSpace@MIT (Massachusetts Institute of Technology).1 indexed citations
17.
Balewski, J., Michael Betancourt, R. Corliss, et al.. (2012). Strangeness Enhancement in Cu-Cu and Au-Au Collisions at √sNN=200 GeV. DSpace@MIT (Massachusetts Institute of Technology).3 indexed citations
18.
Balewski, J., Michael Betancourt, R. Corliss, et al.. (2012). Identified Hadron Compositions in p+p and Au+Au Collisions at High Transverse Momenta at √sNN=200 GeV. DSpace@MIT (Massachusetts Institute of Technology).1 indexed citations
19.
Balewski, J., Michael Betancourt, R. Corliss, et al.. (2012). Directed Flow of Identified Particles in Au+Au Collisions at √SNN=200 GeV at RHIC. DSpace@MIT (Massachusetts Institute of Technology).
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.