Daniel Archambault

2.6k citations
71 papers · 1.4k · h-index 19

Impact in

Papers in

Daniel Archambault

58 papers receiving 1.3k citations

Peers

Daniel Archambault
Comparison fields: 5 of 96
  • Computer Vision and Pattern Recognition 1.1k
  • Statistical and Nonlinear Physics 465
  • Signal Processing 271
  • Computer Graphics and Computer-Aided Design 72
  • Geography, Planning and Development 92
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Danny Holten Netherlands
Fabian Beck Germany
Jörn Kohlhammer Germany
Tatiana von Landesberger Germany
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James Abello United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Archambault

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Archambault

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010175
2 2008108
3 2016104
4 2007103
5 2014101
6 200978
7 201861
8 201543
9 201643
10
Structural differences between two graphs through hierarchies
200934
11 201533
12 201330
13 201128
14 201228
15 201026
16 202026
17 201722
18 200921
19 201619
20 201018

About Daniel Archambault

Daniel Archambault is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Signal Processing, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 71 papers that have together received 1.4k indexed citations. Recurring topics across this work include Data Visualization and Analytics (55 papers), Complex Network Analysis Techniques (20 papers), Data Management and Algorithms (15 papers), Video Analysis and Summarization (11 papers), Topological and Geometric Data Analysis (7 papers), Computational Geometry and Mesh Generation (6 papers), Graph Theory and Algorithms (6 papers) and Advanced Text Analysis Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Statistical and Nonlinear Physics (465 citations), Signal Processing (271 citations), Computer Graphics and Computer-Aided Design (72 citations) and Geography, Planning and Development (92 citations). Daniel Archambault has collaborated with scholars based in United Kingdom, France and Ireland. Frequent co-authors include Helen C. Purchase, David Auber, Tamara Munzner, Bruno Pinaud, Benjamin Bach, Pierre Dragicevic, Christophe Hurter, Sheelagh Carpendale, Paolo Simonetto and Huamin Qu. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Social Networks, Applied Network Science and Information Sciences.

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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