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Found 5 papers, 4 papers with code
Bayesian Additive Main Effects and Multiplicative Interaction Models using Tensor Regression for Multi-environmental Trials
We propose a Bayesian tensor regression model to accommodate the effect of multiple factors on phenotype prediction.
Variational Inference for Additive Main and Multiplicative Interaction Effects Models
In this article, we consider a variational inference approach for such a model.
GP-BART: a novel Bayesian additive regression trees approach using Gaussian processes
The Bayesian additive regression trees (BART) model is an ensemble method extensively and successfully used in regression tasks due to its consistently strong predictive performance and its ability to quantify uncertainty.
Accounting for shared covariates in semi-parametric Bayesian additive regression trees
We propose some extensions to semi-parametric models based on Bayesian additive regression trees (BART).
Bayesian Additive Regression Trees with Model Trees
BART assumes regularisation priors on a set of trees that work as weak learners and is very flexible for predicting in the presence of non-linearity and high-order interactions.
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