Graph Signal Processing
Graph Signal Processing is a mathematical framework that extends classical signal processing techniques to data structured by graphs, enabling the analysis and manipulation of signals defined on the vertices of a graph according to their underlying connectivity patterns.
537
Publications
35.4K
Citations
963
Authors
422
Institutions
Publications per year
2017–2026
377
537
David I Shuman, Sunil K. Narang, Pascal Frossard et al. · IEEE Signal Processing Magazine · 2013 · 4.4K citations · Full text
Graph Signal Processing: Overview, Challenges, and Applications
Antonio Ortega, Pascal Frossard, Jelena Kovačević et al. · Proceedings of the IEEE · 2018 · 1.8K citations · Full text
Discrete Signal Processing on Graphs: Sampling Theory
Siheng Chen, Rohan Varma, Aliaksei Sandryhaila et al. · IEEE Transactions on Signal Processing · 2015 · 668 citations · Full text
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422
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
29 h-index
96 publications
25.6K citations
University of Southern California
Los Angeles, United States
25 h-index
84 publications
17K citations
Carnegie Mellon University
Pittsburgh, United States
24 h-index
72 publications
12.4K citations

Delft University of Technology
Delft, The Netherlands
20 h-index
63 publications
3.6K citations
University of Pennsylvania
Philadelphia, United States
19 h-index
55 publications
4.6K citations
Universidad Rey Juan Carlos
Madrid, Spain
18 h-index
29 publications
1.7K citations
Massachusetts Institute of Technology
Cambridge, United States
18 h-index
34 publications
1.5K citations

Sapienza University of Rome
Rome, Italy
15 h-index
33 publications
2.5K citations
1–8 of 422
83 publications · 10K citations
49
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21 publications · 7.1K citations
19
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Repository · 37 publications · 1.5K citations
18
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24 publications · 839 citations
18
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22 publications · 757 citations
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