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07/30/2023
Stylized Projected GAN: A Novel Architecture for Fast and Realistic Image Generation
Generative Adversarial Networks are used for generating the data using a...
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06/13/2023
Topological Data Analysis for Directed Dependence Networks of Multivariate Time Series Data
Topological data analysis (TDA) approaches are becoming increasingly pop...
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05/31/2023
An MCMC Approach to Bayesian Image Analysis in Fourier Space
Bayesian methods are commonly applied to solve image analysis problems s...
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05/15/2023
Bayesian Nonparametric Multivariate Mixture of Autoregressive Processes: With Application to Brain Signals
One of the goals of neuroscience is to study interactions between differ...
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03/11/2023
Measuring Information Transfer Between Nodes in a Brain Network through Spectral Transfer Entropy
Brain connectivity reflects how different regions of the brain interact ...
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02/20/2023
An Improved Unbiased Particle Filter
In this paper we consider the filtering of partially observed multi-dime...
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01/29/2023
Antithetic Multilevel Particle Filters
In this paper we consider the filtering of partially observed multi-dime...
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12/10/2022
Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation
Common measures of brain functional connectivity (FC) including covarian...
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12/08/2022
Club Exco: clustering brain extreme communities from multi-channel EEG data
Current methods for clustering nodes over time in a brain network are de...
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11/01/2022
Bayesian Parameter Inference for Partially Observed SDEs driven by Fractional Brownian Motion
In this paper we consider Bayesian parameter inference for partially obs...
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09/21/2022
Modeling and Simulating Dependence in Networks Using Topological Data Analysis
Topological data analysis (TDA) approaches are becoming increasingly pop...
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08/07/2022
Granger Causality using Neural Networks
The Granger Causality (GC) test is a famous statistical hypothesis test ...
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08/03/2022
Time-Varying Dispersion Integer-Valued GARCH Models
We propose a general class of INteger-valued Generalized AutoRegressive ...
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07/30/2022
Functional-Coefficient Models for Multivariate Time Series in Designed Experiments: with Applications to Brain Signals
To study the neurophysiological basis of attention deficit hyperactivity...
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04/28/2022
Topological Data Analysis for Multivariate Time Series Data
Over the last two decades, topological data analysis (TDA) has emerged a...
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02/21/2022
Poisson-Birnbaum-Saunders Regression Model for Clustered Count Data
The premise of independence among subjects in the same cluster/group oft...
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07/27/2021
Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification
Brain functional connectivity (FC) reveals biomarkers for identification...
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07/19/2021
BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data
Intrinsic connectivity networks (ICNs) are specific dynamic functional b...
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07/15/2021
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly-Intractable Bayesian Inference
In this paper, a multivariate count distribution with Conway-Maxwell (CO...
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06/09/2021
Markov-Switching State-Space Models with Applications to Neuroimaging
State-space models (SSM) with Markov switching offer a powerful framewor...
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06/02/2021
Filtrated Common Functional Principal Components for Multivariate Functional data
Local field potentials (LFPs) are signals that measure electrical activi...
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05/13/2021
SCAU: Modeling spectral causality for multivariate time series with applications to electroencephalograms
Electroencephalograms (EEG) are noninvasive measurement signals of elect...
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05/01/2021
Topological Data Analysis of COVID-19 Virus Spike Proteins
Topological data analysis, including persistent homology, has undergone ...
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03/31/2021
Spectral Dependence
This paper presents a general framework for modeling dependence in multi...
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03/03/2021
Ridge-penalized adaptive Mantel test and its application in imaging genetics
We propose a ridge-penalized adaptive Mantel test (AdaMant) for evaluati...
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03/02/2021
Time-varying ℓ_0 optimization for Spike Inference from Multi-Trial Calcium Recordings
Optical imaging of genetically encoded calcium indicators is a powerful ...
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02/27/2021
Statistical Inference for Local Granger Causality
Granger causality has been employed to investigate causality relations b...
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02/24/2021
Smooth Online Parameter Estimation for time varying VAR models with application to rat's LFP data
Multivariate time series data appear often as realizations of non-statio...
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02/23/2021
Brain Waves Analysis Via a Non-parametric Bayesian Mixture of Autoregressive Kernels
The standard approach to analyzing brain electrical activity is to exami...
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01/24/2021
Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI
We consider the challenges in extracting stimulus-related neural dynamic...
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01/12/2021
Change-point detection using spectral PCA for multivariate time series
We propose a two-stage approach Spec PC-CP to identify change points in ...
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01/03/2021
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data
Epilepsy is a chronic neurological disorder affecting more than 50 milli...
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11/17/2020
Flexible Bivariate INGARCH Process With a Broad Range of Contemporaneous Correlation
We propose a novel flexible bivariate conditional Poisson (BCP) INteger-...
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07/28/2020
Clustering Brain Signals: A Robust Approach Using Functional Data Ranking
In this paper, we analyze electroencephalograms (EEG) which are recordin...
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07/01/2020
Levels and trends in the sex ratio at birth in seven provinces of Nepal between 1980 and 2016 with probabilistic projections to 2050: a Bayesian modeling approach
Objectives: To estimate sex ratio at birth (SRB) for the seven provinces...
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06/24/2020
Break Point Detection for Functional Covariance
Many experiments record sequential trajectories that oscillate around ze...
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05/19/2020
Multiscale modelling of replicated nonstationary time series
Within the neurosciences, to observe variability across time in the dyna...
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04/23/2020
Semiparametric time series models driven by latent factor
We introduce a class of semiparametric time series models by assuming a ...
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04/18/2020
Integer-valued autoregressive process with flexible marginal and innovation distributions
INteger Auto-Regressive (INAR) processes are usually defined by specifyi...
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04/09/2020
Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach
We present a unified statistical framework for characterizing community ...
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04/09/2020
Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Apporach
We present a unified statistical framework for characterizing community ...
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04/05/2020
Probabilistic Projection of the Sex Ratio at Birth and Missing Female Births by State and Union Territory in India
The sex ratio at birth (SRB) in India has been reported imbalanced since...
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04/02/2020
Classification of Functional Data by Detecting the Discrepancy of Second Moment Structure of Scaled functions
This article presents a new classification method for functional data. W...
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11/27/2019
Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals
A common class of methods for analyzing of multivariate time series, sta...
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10/26/2019
Shape-Preserving Prediction for Stationary Functional Time Series
This article presents a novel method for prediction of stationary functi...
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05/24/2019
Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes
Dynamic functional connectivity, as measured by the time-varying covaria...
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03/21/2019
Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network
We exploit altered patterns in brain functional connectivity as features...
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10/27/2018
Short-segment heart sound classification using an ensemble of deep convolutional neural networks
This paper proposes a framework based on deep convolutional neural netwo...
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10/08/2018
Modeling Brain Connectivity with Graphical Models on Frequency Domain
Multichannel electroencephalograms (EEGs) have been widely used to study...
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09/25/2018
