Topological data analysis

Known as: TDA 
In applied mathematics, Topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology. Extraction of… (More)
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Papers overview

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2018
2018
Statistical analysis on object data presents many challenges. Basic summaries such as means and variances are difficult to… (More)
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2018
2018
Topological data analysis, such as persistent homology has shown beneficial properties for machine learning in many tasks… (More)
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2016
2016
This paper explores the new and growing field of topological data analysis (TDA). TDA is a data analysis method that provides… (More)
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2016
2016
Topological data analysis (TDA) is an emerging mathematical concept for characterizing shapes in complex data. In TDA… (More)
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2016
2016
This work introduces a new dataset and framework for the exploration of topological data analysis (TDA) techniques applied to… (More)
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Highly Cited
2015
Highly Cited
2015
We define a new topological summary for data that we call the persistence landscape. Since this summary lies in a vector space… (More)
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2015
2015
We consider the problem of statistical computations with persistence diagrams, a summary representation of topological features… (More)
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Highly Cited
2015
Highly Cited
2015
Topological data analysis offers a rich source of valuable information to study vision problems. Yet, so far we lack a… (More)
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2012
2012
The extraction of significant structures in arbitrary high-dimensional data sets is a challenging task. Moreover, classifying… (More)
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2011
2011
The theory of zigzag persistence is a substantial extension of persistent homology, and its development has enabled the… (More)
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