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08/17/2023
A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks
Network complexity and computational efficiency have become increasingly...
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03/29/2023
A tensor based varying-coefficient model for multi-modal neuroimaging data analysis
All neuroimaging modalities have their own strengths and limitations. A ...
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09/15/2022
Feature Selection integrated Deep Learning for Ultrahigh Dimensional and Highly Correlated Feature Space
In recent years, deep learning has been a topic of interest in almost al...
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06/01/2022
Sequential Bayesian Neural Subnetwork Ensembles
Deep neural network ensembles that appeal to model diversity have been u...
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01/19/2022
Coupled Support Tensor Machine Classification for Multimodal Neuroimaging Data
Multimodal data arise in various applications where information about th...
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09/03/2021
Variational Bayes algorithm and posterior consistency of Ising model parameter estimation
Ising models originated in statistical physics and are widely used in mo...
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08/25/2021
Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details
Sparse deep neural networks have proven to be efficient for predictive m...
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07/07/2021
ENNS: Variable Selection, Regression, Classification and Deep Neural Network for High-Dimensional Data
High-dimensional, low sample-size (HDLSS) data problems have been a topi...
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06/23/2021
Black Box Variational Bayes Model Averaging
For many decades now, Bayesian Model Averaging (BMA) has been a popular ...
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02/26/2021
TEC: Tensor Ensemble Classifier for Big Data
Tensor (multidimensional array) classification problem has become very p...
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11/19/2020
Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges
Bayesian neural network models (BNN) have re-surged in recent years due ...
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09/28/2020
Quantile Regression Neural Networks: A Bayesian Approach
This article introduces a Bayesian neural network estimation method for ...
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08/15/2020
Ultra high dimensional generalized additive model: Unified Theory and Methods
Generalized additive model is a powerful statistical learning and predic...
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08/11/2020
A Fast, Scalable, and Calibrated Computer Model Emulator: An Empirical Bayes Approach
Mathematical models implemented on a computer have become the driving fo...
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06/29/2020
Statistical Foundation of Variational Bayes Neural Networks
Despite the popularism of Bayesian neural networks in recent years, its ...
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05/03/2020
High Dimensional Classification for Spatially Dependent Data with Application to Neuroimaging
Discriminating patients with Alzheimer's disease (AD) from healthy subje...
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03/28/2020
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration
With the advancements of computer architectures, the use of computationa...
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01/29/2018