
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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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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ENNS: Variable Selection, Regression, Classification and Deep Neural Network for HighDimensional Data
Highdimensional, low samplesize (HDLSS) data problems have been a topi...
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Black Box Variational Bayes Model Averaging
For many decades now, Bayesian Model Averaging (BMA) has been a popular ...
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TEC: Tensor Ensemble Classifier for Big Data
Tensor (multidimensional array) classification problem has become very p...
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Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges
Bayesian neural network models (BNN) have resurged in recent years due ...
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Quantile Regression Neural Networks: A Bayesian Approach
This article introduces a Bayesian neural network estimation method for ...
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Ultra high dimensional generalized additive model: Unified Theory and Methods
Generalized additive model is a powerful statistical learning and predic...
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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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Statistical Foundation of Variational Bayes Neural Networks
Despite the popularism of Bayesian neural networks in recent years, its ...
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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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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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Uncertainty Estimation in Functional Linear Models
Functional data analysis is proved to be useful in many scientific appli...
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Tapabrata Maiti
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