Emmanuel A. Abbe

98 papers receiving 2.1k citations

Emmanuel A. Abbe's Hit Papers

Community Detection and Stochastic Block Models 2018 · 273 citations
2730+2+5Years since publication50100150200250

Peers

Emmanuel A. Abbe
Comparison fields: 5 of 49
  • Health Informatics 128
  • Statistical and Nonlinear Physics 399
  • Computer Networks and Communications 332
  • Computational Mathematics 6
  • Artificial Intelligence 281
Replace Jiaming Xu with:
Jiaming Xu United States
Nikhil Srivastava United States
Xiaojing Ye United States
Alekh Agarwal United States
Igal Sason Israel
Assaf Naor United States
Pascal Bianchi France
Richard Peng United States
Tim J. Sullivan United Kingdom
Ravindran Kannan United States
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Countries citing papers authored by Emmanuel A. Abbe

Since Specialization
Citations

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

Fields of papers citing papers by Emmanuel A. Abbe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emmanuel A. Abbe. 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 Emmanuel A. Abbe. The network helps show where Emmanuel A. Abbe may publish in the future.

Co-authors

The 25 scholars most cited alongside Emmanuel A. Abbe, 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 Emmanuel A. Abbe Line = papers co-authored together Emmanuel A. Abbe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Community Detection and Stochastic Block Models
Hit paper breakdown →
2018273
2 2015171
3 2020112
4 2013102
5 202399
6 201285
7 201468
8 201658
9 201552
10 202052
11 202052
12 200747
13 201447
14 201140
15 201240
16 201839
17 201838
18 201237
19 201537
20 201733

About Emmanuel A. Abbe

Emmanuel A. Abbe is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Artificial Intelligence, Health Informatics and Mathematical Physics, having authored 108 papers that have together received 2.2k indexed citations. Recurring topics across this work include Error Correcting Code Techniques (15 papers), Complex Network Analysis Techniques (12 papers), Coding theory and cryptography (11 papers), Artificial Intelligence in Healthcare and Education (4 papers), Advanced Wireless Communication Techniques (4 papers), Constraint Satisfaction and Optimization (3 papers), Neural Networks and Applications (3 papers) and Stochastic processes and statistical mechanics (2 papers). The work is most often cited by research in Health Informatics (128 citations), Statistical and Nonlinear Physics (399 citations), Computer Networks and Communications (332 citations), Computational Mathematics (6 citations) and Artificial Intelligence (281 citations). Emmanuel A. Abbe has collaborated with scholars based in United States, Switzerland and Israel. Frequent co-authors include Colin Sandon, Emre Telatar, Min Ye, Andrea Montanari A, Amir Shpilka, Amit Singer, Lizhong Zheng, Jianqing Fan, Rémi A. Chou and Matthieu R. Bloch. Their work appears in journals such as IEEE Transactions on Information Theory, The Annals of Statistics, European Heart Journal, EuroIntervention and Information and Inference A Journal of the IMA.

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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