99 citations · 314 across the 26 of their papers we have counts for
4 papers · 1 filter
Generalized Bayes Approach to Inverse Problems with Model Misspecification
Youngsoo Baek, Wilkins Aquino, Sayan Mukherjee
We propose a general framework for obtaining probabilistic solutions to PDE-based inverse problems. Bayesian methods are attractive for uncertainty quantification but assume knowle…
Gaussian Process Mixtures for Estimating Heterogeneous Treatment Effects
Abbas Zaidi, Sayan Mukherjee
We develop a Gaussian-process mixture model for heterogeneous treatment effect estimation that leverages the use of transformed outcomes. The approach we will present attempts to i…
Bayesian Approximate Kernel Regression with Variable Selection
Lorin Crawford, Kris C. Wood, Xiang Zhou +1
Nonlinear kernel regression models are often used in statistics and machine learning because they are more accurate than linear models. Variable selection for kernel regression mod…
The Use of Unlabeled Data in Predictive Modeling
Feng Liang, Sayan Mukherjee, Mike West
The incorporation of unlabeled data in regression and classification analysis is an increasing focus of the applied statistics and machine learning literatures, with a number of re…