Shape Modeling with Spline Partitions. (arXiv:2108.02507v2 [stat.ML] UPDATED)

Shape modelling (with methods that output shapes) is a new and important task
in Bayesian nonparametrics and bioinformatics. In this work, we focus on
Bayesian nonparametric methods for capturing shapes by partitioning a space
using curves. In related work, the classical Mondrian process is used to
partition spaces recursively with axis-aligned cuts, and is widely applied in
multi-dimensional and relational data. The Mondrian process outputs
hyper-rectangles. Recently, the random tessellation process was introduced as a
generalization of the Mondrian process, …

arxiv modeling spline