Showing stat.MEShow all
3 papers · 1 filter
stat.ME2025
Generative Quantile Bayesian Prediction
Maria Nareklishvili, Nick Polson, Vadim Sokolov
Prediction is a central task of machine learning. Our goal is to solve large scale prediction problems using Generative Quantile Bayesian Prediction (GQBP).By directly learning pre…
stat.ME2023
Generative Causal Inference
Maria Nareklishvili, Nicholas Polson, Vadim Sokolov
Generative Bayesian Computation (GBC) methods are developed for Casual Inference. Generative methods are simulation-based methods that use a large training dataset to represent pos…
stat.ME2022
Deep Partial Least Squares for Instrumental Variable Regression
Maria Nareklishvili, Nicholas Polson, Vadim Sokolov
In this paper, we propose deep partial least squares for the estimation of high-dimensional nonlinear instrumental variable regression. As a precursor to a flexible deep neural net…