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Eduardo Pavez
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Cited by
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Graph learning from data under laplacian and structural constraints
HE Egilmez, E Pavez, A Ortega
IEEE Journal of Selected Topics in Signal Processing, 2017
3682017
Generalized Laplacian precision matrix estimation for graph signal processing
E Pavez, A Ortega
IEEE International Conference on Acoustics, Speech and Signal Processing†…, 2016
1222016
Graph learning from filtered signals: Graph system and diffusion kernel identification
HE Egilmez, E Pavez, A Ortega
IEEE Transactions on Signal and Information Processing over Networks 5 (2†…, 2018
652018
Learning graphs with monotone topology properties and multiple connected components
E Pavez, HE Egilmez, A Ortega
IEEE Transactions on Signal Processing 66 (9), 2399-2413, 2018
592018
Dynamic polygon clouds: representation and compression for VR/AR
E Pavez, PA Chou, RL De Queiroz, A Ortega
APSIPA Transactions on Signal and Information Processing 7, 2018
49*2018
Analysis and design of wavelet-packet cepstral coefficients for automatic speech recognition
E Pavez, JF Silva
Speech Communication 54 (6), 814-835, 2012
472012
GTT: Graph Template Transforms with Applications to Image Coding
E Pavez, HE Egilmez, Y Wang, A Ortega
Picture Coding Symposium (PCS), 2015, 199-203, 2015
422015
System and method for inter-frame predictive compression for point clouds
D Tian, E Pavez, R Cohen, A Vetro
US Patent 10,499,054, 2019
342019
Dynamic polygon cloud compression
E Pavez, PA Chou
Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International†…, 2017
302017
Region adaptive graph Fourier transform for 3D point clouds
E Pavez, B Girault, A Ortega, PA Chou
2020 IEEE International Conference on Image Processing (ICIP), 2726-2730, 2020
252020
Covariance matrix estimation with non uniform and data dependent missing observations
E Pavez, A Ortega
IEEE Transactions on Information Theory 67 (2), 1201-1215, 2020
162020
Graph learning with Laplacian constraints: Modeling attractive Gaussian Markov random fields
HE Egilmez, E Pavez, A Ortega
2016 50th Asilomar Conference on Signals, Systems and Computers, 1470-1474, 2016
102016
GLL: Graph Laplacian learning package, version 1.0
HE Egilmez, E Pavez, A Ortega
Graph_Learning, 2017
92017
Two channel filter banks on arbitrary graphs with positive semi definite variation operators
E Pavez, B Girault, A Ortega, PA Chou
IEEE Transactions on Signal Processing 71, 917-932, 2023
82023
A graph learning algorithm based on Gaussian Markov random fields and minimax concave penalty
T Koyakumaru, M Yukawa, E Pavez, A Ortega
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and†…, 2021
82021
Learning separable transforms by inverse covariance estimation
E Pavez, A Ortega, D Mukherjee
International Conference on Image Processing (ICIP) 2017, 2017
82017
Multi-resolution intra-predictive coding of 3d point cloud attributes
E Pavez, AL Souto, RL De Queiroz, A Ortega
2021 IEEE International Conference on Image Processing (ICIP), 3393-3397, 2021
72021
Spectral folding and two-channel filter-banks on arbitrary graphs
E Pavez, B Girault, A Ortega, PA Chou
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and†…, 2021
72021
On learning laplacians of tree structured graphs
KS Lu, E Pavez, A Ortega
2018 IEEE Data Science Workshop (DSW), 205-209, 2018
72018
Learning sparse graph with minimax concave penalty under Gaussian Markov random fields
T Koyakumaru, M Yukawa, E Pavez, A Ortega
IEICE Transactions on Fundamentals of Electronics, Communications and†…, 2023
52023
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