Éric Fabre

1.6k citations
78 papers · 1.2k · h-index 17

Impact in

Papers in

Éric Fabre

75 papers receiving 1.2k citations

Peers

Éric Fabre
Comparison fields: 5 of 35
  • Computational Theory and Mathematics 752
  • Computer Networks and Communications 242
  • Control and Systems Engineering 183
  • Software 22
  • Artificial Intelligence 140
Replace William N. N. Hung with:
William N. N. Hung United States
Yaniv Saʼar Israel
Ahmed Khoumsi Canada
Jussi Rintanen Australia
Akash Deshpande United States
Jǐŕı Srba Denmark
Scott Cotton France
Karen Rudie Canada
A. Udaya Shankar United States
Mark-Oliver Stehr United States
Éric Fabre relative to William N. N. Hung United States William N. N. Hung's profile →
Citations per field
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William N. N. Hung · 1×
Citations per year

Countries citing papers authored by Éric Fabre

Since Specialization
Citations

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

Fields of papers citing papers by Éric Fabre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Éric Fabre. 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 Éric Fabre. The network helps show where Éric Fabre may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003232
2 200195
3 199891
4 200582
5 200343
6 201942
7 200233
8 200329
9 200228
10 200328
11 201028
12 201428
13 200225
14 200923
15 199521
16 200421
17 200721
18 200217
19 200315
20 199613

About Éric Fabre

Éric Fabre is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications, Artificial Intelligence, Software and Control and Systems Engineering, having authored 78 papers that have together received 1.2k indexed citations. Recurring topics across this work include Petri Nets in System Modeling (41 papers), Formal Methods in Verification (13 papers), Software-Defined Networks and 5G (6 papers), AI-based Problem Solving and Planning (6 papers), Fault Detection and Control Systems (6 papers), Mobile Agent-Based Network Management (5 papers), Error Correcting Code Techniques (4 papers) and Bayesian Modeling and Causal Inference (4 papers). The work is most often cited by research in Computational Theory and Mathematics (752 citations), Computer Networks and Communications (242 citations), Control and Systems Engineering (183 citations), Software (22 citations) and Artificial Intelligence (140 citations). Éric Fabre has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Albert Benveniste A, Claude Jard, Stefan Haar, Armen Aghasaryan, Christine M. Guillemot, Arnaud Guyader B, Gregor Gößler, Loı̈c Hélouët, Bernard C. Levy and Paul Le Guernic. Their work appears in journals such as Discrete Event Dynamic Systems, IEEE Transactions on Network and Service Management, IEEE Transactions on Automatic Control, Lecture notes in control and information sciences and Lecture notes in computer science.

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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