David Auber

55 papers receiving 1.2k citations

Peers

David Auber
Comparison fields: 5 of 103
  • Computer Vision and Pattern Recognition 903
  • Statistical and Nonlinear Physics 376
  • Computer Graphics and Computer-Aided Design 91
  • Signal Processing 239
  • Computational Theory and Mathematics 185
Replace Daniel Archambault with:
Daniel Archambault United Kingdom
P. Eades Australia
Danny Holten Netherlands
Chris Muelder United States
Hans‐Jörg Schulz Germany
Kazuo Misue Japan
Nathalie Henry France
Fabian Beck Germany
Mohammad Ghoniem Luxembourg
Kozo Sugiyama Japan
David Auber relative to Daniel Archambault United Kingdom Daniel Archambault's profile →
Citations per field
00.5×1.5×
Daniel Archambault · 1×
Citations per year

Countries citing papers authored by David Auber

Since Specialization
Citations

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

Fields of papers citing papers by David Auber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004204
2 2007118
3 2008118
4 200991
5 200488
6 201087
7 200867
8 201344
9 202342
10 200641
11 200732
12 201722
13 200921
14 202020
15 201119
16 201018
17 200618
18 200618
19 200717
20 202216

About David Auber

David Auber is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Computer Graphics and Computer-Aided Design and Computational Theory and Mathematics, having authored 58 papers that have together received 1.3k indexed citations. Recurring topics across this work include Data Visualization and Analytics (40 papers), Data Management and Algorithms (14 papers), Graph Theory and Algorithms (8 papers), Topological and Geometric Data Analysis (7 papers), Computer Graphics and Visualization Techniques (7 papers), Complex Network Analysis Techniques (7 papers), Multimedia Communication and Technology (6 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (903 citations), Statistical and Nonlinear Physics (376 citations), Computer Graphics and Computer-Aided Design (91 citations), Signal Processing (239 citations) and Computational Theory and Mathematics (185 citations). David Auber has collaborated with scholars based in France, Canada and United Kingdom. Frequent co-authors include Daniel Archambault, Tamara Munzner, Romain Bourqui, Antoine Lambert, Paolo Simonetto, Alexandru Telea, Romain Giot, Jean‐Philippe Domenger, David James Sherman and Bertrand Mathieu. Their work appears in journals such as Computer Graphics Forum, IEEE Transactions on Visualization and Computer Graphics, Visual Informatics, Journal of Graph Algorithms and Applications and Bioinformatics.

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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