Results 21 to 30 of about 127,298 (253)
A topological data analysis based classifier
The paper is under consideration at Advances in Data Analysis and Classification.
Rolando Kindelan +3 more
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Cluster Persistence for Weighted Graphs
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
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Hypothesis testing for topological data analysis [PDF]
14 pages, 5 figures, 1 ...
Andrew Robinson, Katharine Turner
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Neighborhood hypergraph model for topological data analysis
Hypergraph, as a generalization of the notions of graph and simplicial complex, has gained a lot of attention in many fields. It is a relatively new mathematical model to describe the high-dimensional structure and geometric shapes of data sets.
Liu Jian, Chen Dong, Li Jingyan, Wu Jie
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Topological data analysis and cosheaves [PDF]
version 2 has 30 pages, 18 figures; 25 pages, 17 figures, submitted to the Japan Journal of Industrial and Applied ...
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Topological Data Analysis and Clustering
This article is intended to be a chapter for a ...
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Topological data analysis of biological aggregation models. [PDF]
We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms.
Chad M Topaz +2 more
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Empowering Advanced Driver-Assistance Systems from Topological Data Analysis
We are interested in evaluating the state of drivers to determine whether they are attentive to the road or not by using motion sensor data collected from car driving experiments.
Tarek Frahi +7 more
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It has been observed since a long time that data are often carrying interesting topological and geometric structures. Characterizing such structures and providing efficient tools to infer and exploit them is a challenging problem that asks for new mathematics and that is motivated by a real need from applications.
Boissonnat, Jean-Daniel +2 more
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An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying structure has become a problem of fundamental importance for data analysis and statistical learning ...
Frédéric Chazal, Bertrand Michel
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