16 citations · 28 across the 19 of their papers we have counts for
4 papers · 1 filter
Bayesian Causal Forests for Multivariate Outcomes: Application to Irish Data From an International Large Scale Education Assessment
Nathan McJames, Andrew Parnell, Yong Chen Goh +1
Bayesian Causal Forests (BCF) is a causal inference machine learning model based on a highly flexible non-parametric regression and classification tool called Bayesian Additive Reg…
Bayesian Additive Main Effects and Multiplicative Interaction Models using Tensor Regression for Multi-environmental Trials
Antonia A. L. Dos Santos, Danilo A. Sarti, Rafael A. Moral +1
We propose a Bayesian tensor regression model to accommodate the effect of multiple factors on phenotype prediction. We adopt a set of prior distributions that resolve identifiabil…
Variational Inference for Additive Main and Multiplicative Interaction Effects Models
AntÔnia A. L. Dos Santos, Rafael A. Moral, Danilo A. Sarti +1
In plant breeding the presence of a genotype by environment (GxE) interaction has a strong impact on cultivation decision making and the introduction of new crop cultivars. The com…
Accounting for shared covariates in semi-parametric Bayesian additive regression trees
Estevão B. Prado, Andrew C. Parnell, Keefe Murphy +3
We propose some extensions to semi-parametric models based on Bayesian additive regression trees (BART). In the semi-parametric BART paradigm, the response variable is approximated…