Results 31 to 40 of about 7,249,127 (302)
Cluster Persistence for Weighted Graphs
Entropy, 2023 Persistent homology is a natural tool for probing the topological characteristics of weighted graphs, essentially focusing on their 0-dimensional homology.
Omer Bobrowski, Primoz Skraba
doaj +1 more source
Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion [PDF]
npj Systems Biology and Applications, 2022 Different cell types aggregate and sort into hierarchical architectures during the formation of animal tissues. The resulting spatial organization depends (in part) on the strength of adhesion of one cell type to itself relative to other cell types ...
Dhananjay Bhaskar +4 more
semanticscholar +1 more source
Topological data analysis for geographical information science using persistent homology
International Journal of Geographical Information Science, 2023 Topological data analysis (TDA) is an emerging field of research, which considers the application of topology to data analysis. Recently, these methods have been successfully applied to research problems in the field of geographical information science ...
P. Corcoran, Christopher B. Jones
semanticscholar +1 more source
A novel approach for wafer defect pattern classification based on topological data analysis [PDF]
Expert systems with applications, 2022 In semiconductor manufacturing, wafer map defect pattern provides critical information for facility maintenance and yield management, so the classification of defect patterns is one of the most important tasks in the manufacturing process. In this paper,
Seung-Geun Ko, Dowan Koo
semanticscholar +1 more source
On topological data analysis for structural dynamics: an introduction to persistent homology [PDF]
ASME Open Journal of Engineering, 2022 Topological methods can provide a way of proposing new metrics and methods of scrutinizing data, that otherwise may be overlooked. A method of quantifying the shape of data, via a topic called topological data analysis (TDA) will be introduced.
T. Gowdridge, N. Dervilis, K. Worden
semanticscholar +1 more source
Topology and Intelligent Data Analysis [PDF]
Intelligent Data Analysis, 2003 A broad range of mathematical techniques, ranging from statistics to fuzzy logic, have been used to great advantage in intelligent data analysis. Topology – the fundamental mathematics of shape – has to date been conspicuously absent from this repertoire.
Robins, Vanessa +3 more
openaire +1 more source
Dynamic topological data analysis of functional human brain networks [PDF]
Foundations of Data Science, 2022 Developing reliable methods to discriminate different transient brain states that change over time is a key neuroscientific challenge in brain imaging studies.
Moo K. Chung, Soumya Das, H. Ombao
semanticscholar +1 more source
Nature Communications, 2022 In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement or lack a predictable ordered plan remains to be determined.
M. Saggar +4 more
semanticscholar +1 more source
Topological data analysis of vortices in the magnetically-induced current density in LiH molecule [PDF]
Physical Chemistry, Chemical Physics - PCCP, 2022 A novel strategy for extracting axial (AV) and toroidal (TV) vortices in the magnetically-induced current density (MICD) in molecular systems is introduced, and its pilot application to LiH molecule is demonstrated.
M. Olejniczak, Julien Tierny
semanticscholar +1 more source
Persistent Homology and String Vacua [PDF]
, 2015 We use methods from topological data analysis to study the topological features of certain distributions of string vacua. Topological data analysis is a multi-scale approach used to analyze the topological features of a dataset by identifying which ...
Cirafici, Michele
core +3 more sources