The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains DI Shuman, SK Narang, P Frossard, A Ortega, P Vandergheynst
IEEE Signal Processing Magazine 30 (3), 83-98, 2013
4884 2013 Vertex-frequency analysis on graphs DI Shuman, B Ricaud, P Vandergheynst
Applied and Computational Harmonic Analysis 40 (2), 260-291, 2016
453 2016 GSPBOX: A toolbox for signal processing on graphs N Perraudin, J Paratte, D Shuman, L Martin, V Kalofolias, ...
arXiv preprint arXiv:1408.5781, 2014
387 2014 A multiscale pyramid transform for graph signals DI Shuman, MJ Faraji, P Vandergheynst
IEEE Transactions on Signal Processing 64 (8), 2119-2134, 2015
210 * 2015 Chebyshev polynomial approximation for distributed signal processing DI Shuman, P Vandergheynst, P Frossard
2011 International Conference on Distributed Computing in Sensor Systems and …, 2011
184 2011 Spectrum-adapted tight graph wavelet and vertex-frequency frames DI Shuman, C Wiesmeyr, N Holighaus, P Vandergheynst
IEEE Transactions on Signal Processing 63 (16), 4223-4235, 2015
176 2015 A windowed graph Fourier transform DI Shuman, B Ricaud, P Vandergheynst
2012 IEEE Statistical Signal Processing Workshop (SSP), 133-136, 2012
160 2012 Learning parametric dictionaries for signals on graphs D Thanou, DI Shuman, P Frossard
IEEE Transactions on Signal Processing 62 (15), 3849-3862, 2014
149 2014 A wireless soil moisture smart sensor web using physics-based optimal control: Concept and initial demonstrations M Moghaddam, D Entekhabi, Y Goykhman, K Li, M Liu, A Mahajan, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2010
143 2010 Distributed signal processing via Chebyshev polynomial approximation DI Shuman, P Vandergheynst, D Kressner, P Frossard
IEEE Transactions on Signal and Information Processing over Networks 4 (4 …, 2018
138 2018 UNLocBoX: A MATLAB convex optimization toolbox for proximal-splitting methods N Perraudin, V Kalofolias, D Shuman, P Vandergheynst
arXiv preprint arXiv:1402.0779, 2014
96 2014 Global and local uncertainty principles for signals on graphs N Perraudin, B Ricaud, DI Shuman, P Vandergheynst
APSIPA Transactions on Signal and Information Processing 7, e3, 2018
89 2018 Graph filters for signal processing and machine learning on graphs E Isufi, F Gama, DI Shuman, S Segarra
IEEE Transactions on Signal Processing, 2024
77 2024 Graph Signal Processing: History, development, impact, and outlook G Leus, AG Marques, JMF Moura, A Ortega, DI Shuman
IEEE Signal Processing Magazine 40 (4), 49-60, 2023
71 2023 Parametric dictionary learning for graph signals D Thanou, DI Shuman, P Frossard
2013 IEEE Global Conference on Signal and Information Processing, 487-490, 2013
53 2013 Measurement scheduling for soil moisture sensing: From physical models to optimal control DI Shuman, A Nayyar, A Mahajan, Y Goykhman, K Li, M Liu, D Teneketzis, ...
Proceedings of the IEEE 98 (11), 1918-1933, 2010
51 2010 Optimal sleep scheduling for a wireless sensor network node D Shuman, M Liu
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 1337-1341, 2006
47 2006 Localized spectral graph filter frames: A unifying framework, survey of design considerations, and numerical comparison DI Shuman
IEEE Signal Processing Magazine 37 (6), 43-63, 2020
45 2020 Scalable S Li, Y Jin, DI Shuman
IEEE Transactions on Signal Processing 67 (15), 3954-3969, 2019
33 2019 Semi-supervised learning with spectral graph wavelets DI Shuman, M Faraji, P Vandergheynst
Proceedings of the International Conference on Sampling Theory and …, 2011
28 2011 
Pierre VandergheynstProfessor of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL)Dirección de correo verificada de epfl.ch
