| 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 | 3732 | 2013 |
| Vertex-frequency analysis on graphs DI Shuman, B Ricaud, P Vandergheynst Applied and Computational Harmonic Analysis 40 (2), 260-291, 2016 | 369 | 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 | 298 | 2014 |
| A multiscale pyramid transform for graph signals DI Shuman, MJ Faraji, P Vandergheynst IEEE Transactions on Signal Processing 64 (8), 2119-2134, 2015 | 182* | 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 | 153 | 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 | 150 | 2015 |
| A windowed graph Fourier transform DI Shuman, B Ricaud, P Vandergheynst 2012 IEEE Statistical Signal Processing Workshop (SSP), 133-136, 2012 | 145 | 2012 |
| Learning parametric dictionaries for signals on graphs D Thanou, DI Shuman, P Frossard IEEE Transactions on Signal Processing 62 (15), 3849-3862, 2014 | 133 | 2014 |
| 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 | 123 | 2018 |
| 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 | 118 | 2010 |
| UNLocBoX: A MATLAB convex optimization toolbox for proximal-splitting methods N Perraudin, V Kalofolias, D Shuman, P Vandergheynst arXiv preprint arXiv:1402.0779, 2014 | 80 | 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 | 73 | 2018 |
| 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 | 49 | 2006 |
| Parametric dictionary learning for graph signals D Thanou, DI Shuman, P Frossard 2013 IEEE Global Conference on Signal and Information Processing, 487-490, 2013 | 47 | 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 | 41 | 2010 |
| 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 | 33 | 2020 |
| 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 |
| Scalable -Channel Critically Sampled Filter Banks for Graph Signals S Li, Y Jin, DI Shuman IEEE Transactions on Signal Processing 67 (15), 3954-3969, 2019 | 25 | 2019 |
| Energy-efficient transmission scheduling with strict underflow constraints DI Shuman, M Liu, OQ Wu IEEE transactions on information theory 57 (3), 1344-1367, 2011 | 20 | 2011 |
| On the sparsity of wavelet coefficients for signals on graphs B Ricaud, DI Shuman, P Vandergheynst Wavelets and Sparsity XV 8858, 422-428, 2013 | 19 | 2013 |
Pierre VandergheynstProfessor of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
