Carey E. Priebe

8.9k citations
217 papers · 3.7k indexed · 2 hit papers · h-index 34

Carey E. Priebe

207 papers receiving 3.5k citations

Hit Papers

The connectome of an insect...1552017202620202023100200300

Peers

Carey E. Priebe
Comparison fields: 5 of 173
  • Statistical and Nonlinear Physics 746
  • Statistics and Probability 407
  • Artificial Intelligence 1.4k
  • Computational Mathematics 25
  • Computer Vision and Pattern Recognition 746
Replace Boaz Nadler with:
Boaz Nadler Israel
Stéphane Lafon United States
Neil D. Lawrence United Kingdom
Eric D. Kolaczyk United States
Desmond J. Higham United Kingdom
Alex M. Andrew United Kingdom
Shuiwang Ji United States
Naftali Tishby Israel
Joshua T Vogelstein United States
Tom Heskes Netherlands
Carey E. Priebe relative to Boaz Nadler Israel Boaz Nadler's profile →
Citations per field
00.5×1.6×
Boaz Nadler · 1×
Citations per year

Countries citing papers authored by Carey E. Priebe

Since Specialization
Citations

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

Fields of papers citing papers by Carey E. Priebe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carey E. Priebe. 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 Carey E. Priebe. The network helps show where Carey E. Priebe may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Carey E. Priebe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Carey E. Priebe Line = papers co-authored together Carey E. Priebe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20242
3 20232
4
The connectome of an insect brainbreakdown →
2023155
5 20232
6 20232
7 20222
8 20229
9 20222
10 202132
11 20214
12
On identifying unobserved heterogeneity in stochastic blockmodel graphs with vertex covariates.
20201
13 201921
14 20192
15 201820
16 201817
17 2015130
18 2014147
19 200017
20 19997

About Carey E. Priebe

Carey E. Priebe is a scholar working on Statistics and Probability, Statistical and Nonlinear Physics, Artificial Intelligence, Computer Vision and Pattern Recognition and Space and Planetary Science, having authored 217 papers that have together received 3.7k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (49 papers), Bayesian Methods and Mixture Models (30 papers), Face and Expression Recognition (24 papers), Functional Brain Connectivity Studies (22 papers), Advanced Graph Neural Networks (22 papers), Neural Networks and Applications (21 papers), Statistical Methods and Inference (20 papers) and Image Retrieval and Classification Techniques (18 papers). The work is most often cited by research in Statistical and Nonlinear Physics (746 citations), Statistics and Probability (407 citations), Artificial Intelligence (1.4k citations), Computational Mathematics (25 citations) and Computer Vision and Pattern Recognition (746 citations). Carey E. Priebe has collaborated with scholars based in United States, United Kingdom and Türkiye. Frequent co-authors include David J. Marchette, Youngser Park, Minh Tang, Joshua T Vogelstein, Daniel L. Sussman, Donniell E. Fishkind, Vince Lyzinski, John M. Conroy, Jeffrey L. Solka and Marta Zlatic. Their work appears in journals such as Computational Statistics & Data Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Computational and Graphical Statistics, Journal of the American Statistical Association and Journal of Classification.

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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