189 citations · 888 across the 107 of their papers we have counts for
11 papers · 1 filter
Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation
Yee-Fan Tan, Chee-Ming Ting, Fuad Noman +2
Common measures of brain functional connectivity (FC) including covariance and correlation matrices are semi-positive definite (SPD) matrices residing on a cone-shape Riemannian ma…
Club Exco: clustering brain extreme communities from multi-channel EEG data
Matheus B. Guerrero, Paolo V. Redondo, Marco A. Pinto-Orellana +3
Current methods for clustering brain networks over time often rely on cross-dependence measures computed from the entire range of EEG signals, which can obscure information specifi…
Hodge-Decomposition of Brain Networks
D Vijay Anand, D. Vijay Anand, Anass B El-Yaagoubi +2
We analyze brain networks by decomposing them into three orthogonal components: gradient, curl, and harmonic flows, through the Hodge decomposition, a technique advantageous for ca…
Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion
Mohamed Maama, Ajay Jasra, Hernando Ombao
In this paper we consider Bayesian parameter inference for partially observed fractional Brownian motion (fBM) models. The approach we follow is to time-discretize the hidden proce…
Dynamic Topological Data Analysis of Functional Human Brain Networks
Moo K. Chung, Soumya Das, Hernando Ombao
Developing reliable methods to discriminate different transient brain states that change over time is a key neuroscientific challenge in brain imaging studies. Topological data ana…
Modeling and Simulating Dependence in Networks Using Topological Data Analysis
Anass El Yaagoubi Bourakna, Moo K. Chung, Hernando Ombao
Topological data analysis (TDA) approaches are becoming increasingly popular for studying the dependence patterns in multivariate time series data. In particular, various dependenc…
Granger Causality using Neural Networks
Malik Shahid Sultan, Samuel Horvath, Hernando Ombao
Dependence between nodes in a network is an important concept that pervades many areas including finance, politics, sociology, genomics and the brain sciences. One way to character…
Time-Varying Dispersion Integer-Valued GARCH Models
Wagner Barreto-Souza, Luiza S. C. Piancastelli, Konstantinos Fokianos +1
We propose a general class of INteger-valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing time-varying mean and dispersion parameters, w…
Functional-Coefficient Models for Multivariate Time Series in Designed Experiments: with Applications to Brain Signals
Paolo Victor Redondo, Raphael Huser, Hernando Ombao
To study the neurophysiological basis of attention deficit hyperactivity disorder (ADHD), clinicians use electroencephalography (EEG) which record neuronal electrical activity on t…
Topological Data Analysis for Multivariate Time Series Data
Anass El Yaagoubi Bourakna, Moo K. Chung, Hernando Ombao
Over the last two decades, topological data analysis (TDA) has emerged as a very powerful data analytic approach which can deal with various data modalities of varying complexities…
Poisson-Birnbaum-Saunders Regression Model for Clustered Count Data
Jussiane Nader Gonçalves, Wagner Barreto-Souza, Hernando Ombao
The premise of independence among subjects in the same cluster/group often fails in practice, and models that rely on such untenable assumption can produce misleading results. To o…