activity
20162023
most citedIdentification of oscillatory brain networks with Hidden Gaussian Graphical Spectral models of EEG/MEG

9 citations · 20 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ME2023★ 1 cited

Multivariate Intrinsic Local Polynomial Regression on Isometric Riemannian Manifolds: Applications to Positive Definite Data

Ronaldo García Reyes, Ying Wang, Min Li +4

The paper introduces a novel non-parametric Riemannian regression method using Isometric Riemannian Manifolds (IRMs). The proposed technique, Intrinsic Local Polynomial Regression…

stat.ME2022

FKreg: A MATLAB toolbox for fast Multivariate Kernel Regression

Ying Wang, Min Li, Deirel Paz-Linares +2

Kernel smooth is the most fundamental technique for data density and regression estimation. However, time-consuming is the biggest obstacle for the application that the direct eval…

q-bio.NC2018★ 4 cited

Third Generation MEEG Source Connectivity Analysis Toolbox (BC-VARETA 1.0) and Validation Benchmark

Eduardo Gonzalez-Moreira, Deirel Paz-Linares, Ariosky Areces-Gonzalez +2

This paper presents a new toolbox for MEEG source activity and connectivity estimation: Brain Connectivity Variable Resolution Tomographic Analysis version 1.0 (BC-VARETA 1.0). It…

stat.ME2018★ 9 cited

Identification of oscillatory brain networks with Hidden Gaussian Graphical Spectral models of EEG/MEG

Deirel Paz-Linares, Eduardo Gonzalez-Moreira, Ariosky Areces-Gonzalez +7

Identifying the functional networks underpinning indirectly observed processes poses an inverse problem for neurosciences or other fields. A solution of such inverse problems estim…

q-bio.NC2018★ 6 cited

Caulking the Leakage Effect in MEEG Source Connectivity Analysis

Eduardo Gonzalez-Moreira, Deirel Paz-Linares, Ariosky Areces-Gonzalez +4

Simplistic estimation of neural connectivity in MEEG sensor space is impossible due to volume conduction. The only viable alternative is to carry out connectivity estimation in sou…

stat.ME2016

Empirical bayes formulation of the elastic net and mixed-norm models: application to the eeg inverse problem

Deirel Paz-Linares, Mayrim Vega-Hernández, Pedro A. Rojas-López +2

The estimation of EEG generating sources constitutes an Inverse Problem (IP) in Neuroscience. This is an ill-posed problem, due to the non-uniqueness of the solution, and many kind…