  Modern applications of survival analysis increasingly involve time-dependent
covariates. The Python package BoXHED2.0 is a tree-boosted hazard estimator
that is fully nonparametric, and is applicable to survival settings far more
general than right-censoring, including recurring events and competing risks.
BoXHED2.0 is also scalable to the point of being on the same order of speed as
parametric boosted survival models, in part because its core is written in C++
and it also supports the use of GPUs and multicore CPUs. BoXHED2.0 is available
from PyPI and also from www.github.com/BoXHED.
