Computational Topology in
@inproceedings{Stolz2014ComputationalTI,
title={Computational Topology in},
author={Bernadette J. Stolz},
year={2014}
}Computational topology is a set of algorithmic methods developed to understand topological invariants such as loops and holes in high-dimensional data sets. In particular, a method know as persistent homology has been used to understand such shapes and their persistence in point clouds and networks. It has only been applied to neuronal networks in recent years. While most tools from network science focus solely on local properties based on pairwise connections, the topological tools reveal more…
Figures from this paper
figure 1.1 
figure 2.1 
figure 2.2 
figure 2.3 
figure 2.4 
figure 2.5 
figure 2.6 
figure 2.7 
figure 3.1 
figure 3.2 
figure 3.3 
figure 4.1 
figure 4.10 
figure 4.11 
figure 4.12 
figure 4.13 
figure 4.14 
figure 4.15 
figure 4.16 
figure 4.17 
figure 4.2 
figure 4.3 
figure 4.4 
figure 4.5 
figure 4.6 
figure 4.7 
figure 4.8 
figure 4.9 
figure B.1 
figure B.2 
figure B.3 
figure B.4 
figure B.5 
figure B.6 
figure B.7
One Citation
Topological Data Analysis for Systems of Coupled Oscillators
- Computer Science
- 2016
By looking for clustering in a data space consisting of the phase change of oscillators over a set of time delays it is hoped to reconstruct attractors and identify members of these clusters.
References
SHOWING 1-10 OF 29 REFERENCES
jHoles: A Tool for Understanding Biological Complex Networks via Clique Weight Rank Persistent Homology
- Computer ScienceCS2Bio
- 2014
Persistent Homology — a Survey
- Mathematics
Persistent homology is an algebraic tool for measuring topological features of shapes and functions. It casts the multi-scale organization we frequently observe in nature into a mathematical…
Discriminative persistent homology of brain networks
- Biology2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
- 2011
This paper applies the Rips filtration to construct the FDG-PET based functional brain networks out of 24 attention deficit hyperactivity disorder (ADHD) children, 26 autism spectrum disorder (ASD) children and 11 pediatric control subjects and visually shows the topological evolution of the brain networks using the barcode and performs statistical inference on the group differences.
Barcodes: The persistent topology of data
- Mathematics
- 2007
This article surveys recent work of Carlsson and collaborators on applications of computational algebraic topology to problems of feature detection and shape recognition in high-dimensional data. The…
javaPlex: A Research Software Package for Persistent (Co)Homology
- MathematicsICMS
- 2014
A new software package for topological computation, replacing previous jPlex and Plex, enables researchers to access state of the art algorithms for persistent homology, cohomology, hom complexes, filtered simplicial complex, filtered cell complexes, witness complex constructions, and many more essential components of computational topology.
Topology and data
- Computer Science
- 2009
This paper will discuss how geometry and topology can be applied to make useful contributions to the analysis of various kinds of data, particularly high throughput data from microarray or other sources.
Weighted Functional Brain Network Modeling via Network Filtration
- Computer Science
- 2012
The proposed network filtration framework can discriminate the local and global differences of the brain networks of 24 attention deficit hyperactivity disorder (ADHD), 26 autism spectrum disorder (ASD) and 11 pediatric control (PedCon) children obtained through the FDG-PET data.
A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology
- BiologyPLoS Comput. Biol.
- 2012
Using a computational algorithm based on recently developed tools from Persistent Homology theory in the field of algebraic topology, it is found that the patterns of neuronal co-firing can, in fact, convey topological information about the environment in a biologically realistic length of time.
Topological Persistence and Simplification
- EconomicsProceedings 41st Annual Symposium on Foundations of Computer Science
- 2000
Fast algorithms for computing persistence and experimental evidence for their speed and utility are given for topological simplification within the framework of a filtration, which is the history of a growing complex.