9 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
Fully Nonparametric Bayesian Additive Regression Trees
Edward George, Prakash Laud, Brent Logan +2
Bayesian Additive Regression Trees (BART) is a fully Bayesian approach to modeling with ensembles of trees. BART can uncover complex regression functions with high dimensional regr…
Nonparametric competing risks analysis using Bayesian Additive Regression Trees (BART)
Rodney Sparapani, Brent R. Logan, Robert E. McCulloch +1
Many time-to-event studies are complicated by the presence of competing risks. Such data are often analyzed using Cox models for the cause specific hazard function or Fine-Gray mod…
Additivity Assessment in Nonparametric Models Using Ratio of Pseudo Marginal Likelihoods
Bonifride Tuyishimire, Brent R Logan, Purushottam W Laud
Nonparametric regression models such as Bayesian Additive Regression Trees (BART) can be useful in fitting flexible functions of a set of covariates to a response, while accounting…
Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data
Ning Liu, Ying Liu, Brent Logan +3
This paper presents the first deep reinforcement learning (DRL) framework to estimate the optimal Dynamic Treatment Regimes from observational medical data. This framework is more…