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09/05/2023
Adaptive Bayesian Predictive Inference
Bayesian predictive inference provides a coherent description of entire ...
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05/31/2023
On Mixing Rates for Bayesian CART
The success of Bayesian inference with MCMC depends critically on Markov...
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08/25/2022
Adversarial Bayesian Simulation
In the absence of explicit or tractable likelihoods, Bayesians often res...
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05/30/2022
Deep Bootstrap for Bayesian Inference
For a Bayesian, the task to define the likelihood can be as perplexing a...
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11/22/2021
Approximate Bayesian Computation via Classification
Approximate Bayesian Computation (ABC) enables statistical inference in ...
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05/26/2021
Ideal Bayesian Spatial Adaptation
Many real-life applications involve estimation of curves that exhibit co...
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03/06/2021
Metropolis-Hastings via Classification
This paper develops a Bayesian computational platform at the interface b...
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11/29/2020
Bayesian Bootstrap Spike-and-Slab LASSO
The impracticality of posterior sampling has prevented the widespread ad...
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10/13/2020
Spike-and-Slab Meets LASSO: A Review of the Spike-and-Slab LASSO
High-dimensional data sets have become ubiquitous in the past few decade...
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08/15/2020
The art of BART: On flexibility of Bayesian forests
Considerable effort has been directed to developing asymptotically minim...
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07/01/2020
Variable Selection via Thompson Sampling
Thompson sampling is a heuristic algorithm for the multi-armed bandit pr...
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02/26/2020
Uncertainty Quantification for Sparse Deep Learning
Deep learning methods continue to have a decided impact on machine learn...
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10/16/2019
Multiscale Analysis of Bayesian CART
This paper affords new insights about Bayesian CART in the context of st...
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09/14/2019
Adaptive Bayesian SLOPE – High-dimensional Model Selection with Missing Values
The selection of variables with high-dimensional and missing data is a m...
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05/09/2019
On Semi-parametric Bernstein-von Mises Theorems for BART
Few methods in Bayesian non-parametric statistics/ machine learning have...
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12/11/2018
Dynamic Sparse Factor Analysis
Its conceptual appeal and effectiveness has made latent factor modeling ...
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10/01/2018
On Theory for BART
Ensemble learning is a statistical paradigm built on the premise that ma...
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07/22/2018
The Median Probability Model and Correlated Variables
The median probability model (MPM) Barbieri and Berger (2004) is defined...
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06/06/2018
ABC Variable Selection with Bayesian Forests
Few problems in statistics are as perplexing as variable selection in th...
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03/24/2018
Posterior Concentration for Sparse Deep Learning
Spike-and-Slab Deep Learning (SS-DL) is a fully Bayesian alternative to ...
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01/09/2018