activity
20192026
most citedTowards Stratified Space Learning: Linearly Embedded Graphs

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CG2026

Quadratic Forms for Measuring Geometric Trees in 3-dimensional Space

Yossi Bokor Bleile, Emanuele Cortinovis, Herbert Edelsbrunner +1

Tree-like structures appear in many areas of science, and their shapes can help understand the underlying processes they drive or that give rise to them. By thinking of these struc…

q-bio.OT2026

Persistent Homology as a Morphological Signature of Fibrin Networks

Thomas Burnett, Theresa Reinhold, Bea Bleile +5

We present an investigation of the applicability of topological data analysis (TDA) to the study of high-resolution confocal microscopy images of fibrin network structures from pat…

math.AT2025

Identifying cobordisms using kernel persistence

Yossi Bokor Bleile, Lisbeth Fajstrup, Teresa Heiss +2

Motivated by applications in chemistry, we give a homlogical definition of tunnels, or more generally cobordisms, connecting disjoint parts of a cell complex. For a filtered comple…

math.AT2021★ 4 cited

Towards Stratified Space Learning: Linearly Embedded Graphs

Yossi Bokor, Katharine Turner, Christopher Williams

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…

math.AT2019

Stratified Space Learning: Reconstructing Embedded Graphs

Yossi Bokor, Daniel Grixti-Cheng, Markus Hegland +2

Many data-rich industries are interested in the efficient discovery and modelling of structures underlying large data sets, as it allows for the fast triage and dimension reduction…