Ryan P. Browne

1.3k total citations
48 papers, 599 citations indexed

About

Ryan P. Browne is a scholar working on Artificial Intelligence, Statistics and Probability and Statistics, Probability and Uncertainty. According to data from OpenAlex, Ryan P. Browne has authored 48 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 24 papers in Statistics and Probability and 9 papers in Statistics, Probability and Uncertainty. Recurrent topics in Ryan P. Browne's work include Bayesian Methods and Mixture Models (33 papers), Advanced Clustering Algorithms Research (17 papers) and Statistical Methods and Bayesian Inference (11 papers). Ryan P. Browne is often cited by papers focused on Bayesian Methods and Mixture Models (33 papers), Advanced Clustering Algorithms Research (17 papers) and Statistical Methods and Bayesian Inference (11 papers). Ryan P. Browne collaborates with scholars based in Canada, Italy and United States. Ryan P. Browne's co-authors include Paul D. McNicholas, Brian C. Franczak, Paula Murray, Utkarsh J. Dang, Stefan Steiner, Robert J. MacKay, Cristina Tortora, Antonio Punzo, Nathaniel T. Stevens and Sanjeena Subedi and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Technometrics and Biometrics.

In The Last Decade

Ryan P. Browne

42 papers receiving 583 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ryan P. Browne Canada 12 442 301 59 54 49 48 599
Myoungshic Jhun South Korea 13 160 0.4× 368 1.2× 23 0.4× 44 0.8× 20 0.4× 49 553
Haeran Cho United Kingdom 10 101 0.2× 196 0.7× 31 0.5× 26 0.5× 38 0.8× 24 438
Ansgar Steland Germany 11 64 0.1× 208 0.7× 26 0.4× 39 0.7× 9 0.2× 72 411
Ronald Bremer United States 8 101 0.2× 113 0.4× 36 0.6× 16 0.3× 10 0.2× 19 350
Rosanna Verde Italy 11 213 0.5× 68 0.2× 70 1.2× 58 1.1× 11 0.2× 30 383
Xiaohai Sun Germany 6 207 0.5× 97 0.3× 27 0.5× 44 0.8× 30 0.6× 9 387
Hans Hermann Bock Germany 6 227 0.5× 89 0.3× 73 1.2× 33 0.6× 19 0.4× 9 369
Aqib Ali Pakistan 10 100 0.2× 47 0.2× 5 0.1× 39 0.7× 20 0.4× 33 492
Tiefeng Ma China 10 97 0.2× 126 0.4× 21 0.4× 33 0.6× 7 0.1× 50 274

Countries citing papers authored by Ryan P. Browne

Since Specialization
Citations

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

Fields of papers citing papers by Ryan P. Browne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan P. Browne. 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 Ryan P. Browne. The network helps show where Ryan P. Browne may publish in the future.

Co-authorship network of co-authors of Ryan P. Browne

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan P. Browne. A scholar is included among the top collaborators of Ryan P. Browne 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 Ryan P. Browne. Ryan P. Browne 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
1.
2.
Browne, Ryan P., et al.. (2024). A mixture of logistic skew-normal multinomial models. Computational Statistics & Data Analysis. 196. 107946–107946.
3.
Dang, Utkarsh J., et al.. (2023). Model-Based Clustering and Classification Using Mixtures of Multivariate Skewed Power Exponential Distributions. Journal of Classification. 40(1). 145–167. 5 indexed citations
4.
Browne, Ryan P., Luca Bagnato, & Antonio Punzo. (2023). Parsimony and parameter estimation for mixtures of multivariate leptokurtic-normal distributions. Advances in Data Analysis and Classification. 18(3). 597–625. 1 indexed citations
5.
Browne, Ryan P., et al.. (2023). Flexible mixture regression with the generalized hyperbolic distribution. Advances in Data Analysis and Classification. 18(1). 33–60. 1 indexed citations
6.
Browne, Ryan P., et al.. (2023). Generalized linear models for massive data via doubly-sketching. Statistics and Computing. 33(5). 1 indexed citations
7.
Browne, Ryan P., et al.. (2023). Model-Based Clustering with Nested Gaussian Clusters. Journal of Classification. 41(1). 39–64. 1 indexed citations
8.
Browne, Ryan P., et al.. (2021). Functional data clustering by projection into latent generalized hyperbolic subspaces. Advances in Data Analysis and Classification. 15(3). 735–757. 4 indexed citations
9.
10.
Browne, Ryan P., et al.. (2018). Flexible clustering of high-dimensional data via mixtures of joint generalized hyperbolic distributions: Mixtures of joint generalized hyperbolic distributions. arXiv (Cornell University). 7(1). 3 indexed citations
11.
Murray, Paula, Ryan P. Browne, & Paul D. McNicholas. (2017). Hidden truncation hyperbolic distributions, finite mixtures thereof, and their application for clustering. Journal of Multivariate Analysis. 161. 141–156. 10 indexed citations
12.
Franczak, Brian C., John C. Castura, Ryan P. Browne, Christopher J. Findlay, & Paul D. McNicholas. (2016). Handling missing data in consumer hedonic tests arising from direct scaling. Journal of Sensory Studies. 31(6). 514–523. 3 indexed citations
13.
Dang, Utkarsh J., Ryan P. Browne, & Paul D. McNicholas. (2015). Mixtures of Multivariate Power Exponential Distributions. Biometrics. 71(4). 1081–1089. 42 indexed citations
14.
Tortora, Cristina, Brian C. Franczak, Ryan P. Browne, & Paul D. McNicholas. (2014). Mixtures of Multiple Scaled Generalized Hyperbolic Distributions. arXiv (Cornell University). 2 indexed citations
15.
Tortora, Cristina, Brian C. Franczak, Ryan P. Browne, & Paul D. McNicholas. (2014). Model-Based Clustering Using Mixtures of Coalesced Generalized Hyperbolic Distributions. arXiv (Cornell University). 1 indexed citations
16.
Franczak, Brian C., Ryan P. Browne, & Paul D. McNicholas. (2014). Mixtures of Shifted AsymmetricLaplace Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(6). 1149–1157. 87 indexed citations
17.
Stevens, Nathaniel T., Stefan Steiner, Ryan P. Browne, & Robert J. MacKay. (2012). Gauge R&R studies that incorporate baseline information. IIE Transactions. 45(11). 1166–1175. 8 indexed citations
18.
Browne, Ryan P., et al.. (2011). Model-Based Learning Using a Mixture of Mixtures of Gaussian and Uniform Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(4). 814–817. 48 indexed citations
19.
Browne, Ryan P., Jock MacKay, & Stefan Steiner. (2010). Leveraged Gauge R&R Studies - Supplementary Material. Technometrics. 52. 1 indexed citations
20.
Browne, Ryan P., Stefan Steiner, & Robert J. MacKay. (2009). Optimal two‐stage reliability studies. Statistics in Medicine. 29(2). 229–235. 2 indexed citations

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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