Long-lived topological features are distinguished from short-lived ones (considered as topological noise) in simplicial complexes constructed from complex networks. A new topological invariant, persistent homology, is determined and presented as a parameterized version of a Betti number. Complex networks with distinct degree distributions exhibit distinct persistent topological features. Persistent topological attributes, shown to be related to the robust quality of networks, also reflect the deficiency in certain connectivity properties of networks. Random networks, networks with exponential connectivity distribution and scale-free networks were considered for homological persistency analysis
Topological methods can provide a way of proposing new metrics and methods of scrutinizing data, tha...
International audienceThis article introduces an algorithm to compute the persistent homology of a f...
ABSTRACT. Persistent homology is an algebraic tool for measuring topological features of shapes and ...
Persistent homology is an emerging tool to identify robust topological features underlying the stru...
In this position paper, we present a brief overview of the ways topological tools, in particular per...
Topological data analysis is a branch of computational topology which uses algebra to obtain topolo...
Topological data analysis (TDA) is a young field that has been rapidly growing over the last years ...
In this paper we examine the use of topological methods for multivariate statistics. Using persisten...
Topological methods can provide a way of proposing new metrics and methods of scrutinising data, tha...
Homology gives a tool to measure the "holes" in topological spaces. Persistent homology extends the ...
2012 Spring.Includes bibliographical references.In this paper we introduce and explore the idea of p...
Simplicial complexes are used in topological data analysis (TDA) to extract topological features of ...
Este trabajo es un esfuerzo por resumir los principios de la homologia persistente y explicar sus in...
International audienceComputational topology has recently seen an important development toward data ...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...
Topological methods can provide a way of proposing new metrics and methods of scrutinizing data, tha...
International audienceThis article introduces an algorithm to compute the persistent homology of a f...
ABSTRACT. Persistent homology is an algebraic tool for measuring topological features of shapes and ...
Persistent homology is an emerging tool to identify robust topological features underlying the stru...
In this position paper, we present a brief overview of the ways topological tools, in particular per...
Topological data analysis is a branch of computational topology which uses algebra to obtain topolo...
Topological data analysis (TDA) is a young field that has been rapidly growing over the last years ...
In this paper we examine the use of topological methods for multivariate statistics. Using persisten...
Topological methods can provide a way of proposing new metrics and methods of scrutinising data, tha...
Homology gives a tool to measure the "holes" in topological spaces. Persistent homology extends the ...
2012 Spring.Includes bibliographical references.In this paper we introduce and explore the idea of p...
Simplicial complexes are used in topological data analysis (TDA) to extract topological features of ...
Este trabajo es un esfuerzo por resumir los principios de la homologia persistente y explicar sus in...
International audienceComputational topology has recently seen an important development toward data ...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...
Topological methods can provide a way of proposing new metrics and methods of scrutinizing data, tha...
International audienceThis article introduces an algorithm to compute the persistent homology of a f...
ABSTRACT. Persistent homology is an algebraic tool for measuring topological features of shapes and ...