Hernando C. Ombao

Orcid: 0000-0001-7020-8091

Affiliations:
  • King Abdullah University of Science and Technology, Statistics Program, Thuwal, Saudi Arabia


According to our database1, Hernando C. Ombao authored at least 76 papers between 2002 and 2024.

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Bibliography

2024
Assessment of Fractal Synchronization during an Epileptic Seizure.
Entropy, August, 2024

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification.
IEEE J. Biomed. Health Informatics, March, 2024

An improved unbiased particle filter.
Monte Carlo Methods Appl., 2024

Dynamic topological data analysis: a novel fractal dimension-based testing framework with application to brain signals.
Frontiers Neuroinformatics, 2024

Classification of High-dimensional Time Series in Spectral Domain using Explainable Features.
CoRR, 2024

Dynamic MRI reconstruction using low-rank plus sparse decomposition with smoothness regularization.
CoRR, 2024

Topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity.
Proceedings of the Topology- and Graph-Informed Imaging Informatics, 2024

fMRI Functional Connectivity Augmentation Using Convolutional Generative Adversarial Networks for Brain Disorder Classification.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

BrainFC-CGAN: A Conditional Generative Adversarial Network for Brain Functional Connectivity Augmentation and Aging Synthesis.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Topological Data Analysis for Multivariate Time Series Data.
Entropy, November, 2023

Editorial for the special issue on Time Series Analysis.
Comput. Stat. Data Anal., May, 2023

Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference.
J. Comput. Graph. Stat., April, 2023

Statistical inference for dependence networks in topological data analysis.
Frontiers Artif. Intell., February, 2023

Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion.
Stat. Comput., 2023

Stylized Projected GAN: A Novel Architecture for Fast and Realistic Image Generation.
CoRR, 2023

Antithetic Multilevel Particle Filters.
CoRR, 2023

A Unified Framework for Static and Dynamic Functional Connectivity Augmentation for Multi-Domain Brain Disorder Classification.
Proceedings of the IEEE International Conference on Image Processing, 2023

2022
Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI.
IEEE Trans. Medical Imaging, 2022

Brain waves analysis via a non-parametric Bayesian mixture of autoregressive kernels.
Comput. Stat. Data Anal., 2022

Wavelet testing for a replicate-effect within an ordered multiple-trial experiment.
Comput. Stat. Data Anal., 2022

Markov-switching state-space models with applications to neuroimaging.
Comput. Stat. Data Anal., 2022

Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation.
CoRR, 2022

Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion.
CoRR, 2022

Granger Causality using Neural Networks.
CoRR, 2022

Graph Autoencoder-Based Embedded Learning in Dynamic Brain Networks for Autism Spectrum Disorder Identification.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Frequency-Specific Non-Linear Granger Causality in a Network of Brain Signals.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach.
IEEE Trans. Medical Imaging, 2021

Multi-Chaotic Analysis of Inter-Beat (R-R) Intervals in Cardiac Signals for Discrimination between Normal and Pathological Classes.
Entropy, 2021

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification.
CoRR, 2021

Topological Data Analysis of COVID-19 Virus Spike Proteins.
CoRR, 2021

Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI.
CoRR, 2021

Clustering Brain Signals: a Robust Approach Using Functional Data Ranking.
J. Classif., 2021

Lattice Paths for Persistent Diagrams.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data, 2021

2020
Multi-Scale Factor Analysis of High-Dimensional Functional Connectivity in Brain Networks.
IEEE Trans. Netw. Sci. Eng., 2020

Inference on Long-Range Temporal Correlations in Human EEG Data.
IEEE J. Biomed. Health Informatics, 2020

A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns.
IEEE J. Biomed. Health Informatics, 2020

A Markov-Switching Model Approach to Heart Sound Segmentation and Classification.
IEEE J. Biomed. Health Informatics, 2020

Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals.
Entropy, 2020

2019
Evaluation of monofractal and multifractal properties of inter-beat (R-R) intervals in cardiac signals for differentiation between the normal and pathology classes.
IET Signal Process., 2019

Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network.
CoRR, 2019

Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Exploratory Analysis of Brain Signals through Low Dimensional Embedding.
Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Classification of EEG-based Effective Brain Connectivity in Schizophrenia using Deep Neural Networks.
Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Modeling Local Field Potentials with Regularized Matrix Data Clustering.
Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Detecting State Changes in Community Structure of Functional Brain Networks Using a Markov-Switching Stochastic Block Model.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Estimating Brain Connectivity Using Copula Gaussian Graphical Models.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Statistical Persistent Homology of Brain Signals.
Proceedings of the IEEE International Conference on Acoustics, 2019

Short-segment Heart Sound Classification Using an Ensemble of Deep Convolutional Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models.
IEEE Trans. Medical Imaging, 2018

Dynamic classification using multivariate locally stationary wavelet processes.
Signal Process., 2018

Statistical models for brain signals with properties that evolve across trials.
NeuroImage, 2018

Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States.
J. Classif., 2018

The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure.
J. Classif., 2018

2017
A Unified Estimation Framework for State-Related Changes in Effective Brain Connectivity.
IEEE Trans. Biomed. Eng., 2017

A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data.
Brain Connect., 2017

2016
Modeling Effective Connectivity in High-Dimensional Cortical Source Signals.
IEEE J. Sel. Top. Signal Process., 2016

2015
Simultaneous control of error rates in fMRI data analysis.
NeuroImage, 2015

Topological seizure origin detection in electroencephalographic signals.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2014
Estimating Time-Evolving Partial Coherence Between Signals via Multivariate Locally Stationary Wavelet Processes.
IEEE Trans. Signal Process., 2014

A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons.
Neural Comput., 2014

2013
Modeling and Estimation of Covariance of Replicated Modulated Cyclical Time Series.
IEEE Trans. Signal Process., 2013

Quantifying temporal correlations: A test-retest evaluation of functional connectivity in resting-state fMRI.
NeuroImage, 2013

Hierarchical vector auto-regressive models and their applications to multi-subject effective connectivity.
Frontiers Comput. Neurosci., 2013

2012
Investigating brain connectivity using mixed effects vector autoregressive models.
NeuroImage, 2012

2011
Introduction to the special issue on best papers from the SLDM competition.
Stat. Anal. Data Min., 2011

Penalized least squares regression methods and applications to neuroimaging.
NeuroImage, 2011

2010
Functional connectivity: Shrinkage estimation and randomization test.
NeuroImage, 2010

2008
Evolutionary Coherence of Nonstationary Signals.
IEEE Trans. Signal Process., 2008

Sequential Change-Point Detection Methods for Nonstationary Time Series.
Technometrics, 2008

Time-frequency discriminant analysis of MEG signals.
NeuroImage, 2008

2006
Minimax Adaptive Spectral Estimation From an Ensemble of Signals.
IEEE Trans. Signal Process., 2006

Classification of functional brain images with a spatio-temporal dissimilarity map.
NeuroImage, 2006

Time-dependent frequency domain principal components analysis of multichannel non-stationary signals.
Comput. Stat. Data Anal., 2006

2005
Comparing extent of activation: a robust permutation approach.
NeuroImage, 2005

2003
Statistical tests for fMRI based on experimental randomization.
NeuroImage, 2003

2002
Time-frequency spectral estimation of multichannel EEG using the Auto-SLEX method.
IEEE Trans. Biomed. Eng., 2002


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