  In this paper, we consider the simplest class of stratified spaces --
linearly embedded graphs. We present an algorithm that learns the abstract
structure of an embedded graph and models the specific embedding from a point
cloud sampled from it. We use tools and inspiration from computational
geometry, algebraic topology, and topological data analysis and prove the
correctness of the identified abstract structure under assumptions on the
embedding. The algorithm is implemented in the Julia package
http://github.com/yossibokor/Skyler.jl , which we used for the numerical
simulations in this paper.
