Articles with public access mandates - Eduardo PavezLearn more
Not available anywhere: 3
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
Mandates: US National Science Foundation
On learning laplacians of tree structured graphs
KS Lu, E Pavez, A Ortega
2018 IEEE Data Science Workshop (DSW), 205-209, 2018
Mandates: US National Science Foundation
Orthogonality and zero DC tradeoffs in biorthogonal graph filterbanks
DEO Tzamarias, E Pavez, B Girault, A Ortega, I Blanes, J Serra-Sagristà
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
Mandates: Government of Spain
Available somewhere: 15
Graph learning from data under laplacian and structural constraints
HE Egilmez, E Pavez, A Ortega
IEEE Journal of Selected Topics in Signal Processing, 2017
Mandates: US National Science Foundation
Generalized Laplacian precision matrix estimation for graph signal processing
E Pavez, A Ortega
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2016
Mandates: US National Science Foundation
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
Mandates: US National Science Foundation
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
Mandates: US National Science Foundation
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
Mandates: US National Science Foundation
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
Mandates: US National Science Foundation
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
Mandates: US National Science Foundation
Learning separable transforms by inverse covariance estimation
E Pavez, A Ortega, D Mukherjee
International Conference on Image Processing (ICIP) 2017, 2017
Mandates: US National Science Foundation
Laplacian constrained precision matrix estimation: Existence and high dimensional consistency
E Pavez
International Conference on Artificial Intelligence and Statistics, 9711-9722, 2022
Mandates: US National Science Foundation
Fractional motion estimation for point cloud compression
H Hong, E Pavez, A Ortega, R Watanabe, K Nonaka
2022 Data Compression Conference (DCC), 369-378, 2022
Mandates: US National Science Foundation
Motion estimation and filtered prediction for dynamic point cloud attribute compression
H Hong, E Pavez, A Ortega, R Watanabe, K Nonaka
2022 Picture Coding Symposium (PCS), 139-143, 2022
Mandates: US National Science Foundation
An efficient algorithm for graph laplacian optimization based on effective resistances
E Pavez, A Ortega
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 51-55, 2019
Mandates: US National Science Foundation
Active covariance estimation by random sub-sampling of variables
E Pavez, A Ortega
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
Mandates: US National Science Foundation
Point Cloud Attribute Compression Via Chroma Subsampling
SN Sridhara, E Pavez, A Ortega, R Watanabe, K Nonaka
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
Mandates: US National Science Foundation
Learning graphs with monotone topology properties
E Pavez, HE Egilmez, A Ortega
GlobalSIP, 2017
Mandates: US National Science Foundation
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