5 citations · 7 across the 3 of their papers we have counts for
3 papers · 1 filter
Stochastic Tree Ensembles for Estimating Heterogeneous Effects
Nikolay Krantsevich, Jingyu He, P. Richard Hahn
Determining subgroups that respond especially well (or poorly) to specific interventions (medical or policy) requires new supervised learning methods tailored specifically for caus…
XBART: Accelerated Bayesian Additive Regression Trees
Jingyu He, Saar Yalov, P. Richard Hahn
Bayesian additive regression trees (BART) (Chipman et. al., 2010) is a powerful predictive model that often outperforms alternative models at out-of-sample prediction. BART is espe…
Deep Learning for Predicting Asset Returns
Guanhao Feng, Jingyu He, Nicholas G. Polson
Deep learning searches for nonlinear factors for predicting asset returns. Predictability is achieved via multiple layers of composite factors as opposed to additive ones. Viewed i…