David Auber

40 papers receiving 838 citations

Peers

David Auber
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 632
  • Statistical and Nonlinear Physics 262
  • Signal Processing 172
  • Computer Graphics and Computer-Aided Design 54
  • Computational Theory and Mathematics 140
Replace P. Eades with:
P. Eades Australia
Seok-Hee Hong Australia
Nathalie Henry France
Daniel Archambault United Kingdom
Hans‐Jörg Schulz Germany
Chris Muelder United States
Kwan-Liu Ma United States
Kai Xu United Kingdom
Bruno Pinaud France
S. Havre United States
David Auber relative to P. Eades Australia P. Eades's profile →
Citations per field
00.5×10.6×
P. Eades · 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 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008108
2 2007103
3 200978
4 200475
5 201074
6 200864
7 201343
8 202341
9 200725
10 200921
11 202020
12 201018
13 200617
14 200715
15 202014
16 201114
17 200614
18 202214
19 200613
20 201712

About David Auber

David Auber is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics, having authored 43 papers that have together received 870 indexed citations. Recurring topics across this work include Data Visualization and Analytics (30 papers), Data Management and Algorithms (10 papers), Graph Theory and Algorithms (7 papers), Topological and Geometric Data Analysis (6 papers), Complex Network Analysis Techniques (5 papers), Video Analysis and Summarization (4 papers), Computer Graphics and Visualization Techniques (4 papers) and Multimedia Communication and Technology (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (632 citations), Statistical and Nonlinear Physics (262 citations), Signal Processing (172 citations), Computer Graphics and Computer-Aided Design (54 citations) and Computational Theory and Mathematics (140 citations). David Auber has collaborated with scholars based in France, Canada and United States. Frequent co-authors include Daniel Archambault, Tamara Munzner, Romain Bourqui, Alexandru Telea, Antoine Lambert, Paolo Simonetto, Romain Giot, David James Sherman, Bertrand Mathieu and Macha Nikolski. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Visual Informatics, Journal of Graph Algorithms and Applications and Informatics.

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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