One-dimensional persistent homology is arguably the most important and heavily used computational tool in topological data analysis. Additional information can be extracted from datasets by studying multi-dimensional persistence modules and by utilizing cohomological ideas, e.g.~the cohomological cup product. In this work, given a single parameter filtration, we investigate a certain 2-dimensional persistence module structure associated with persistent cohomology, where one parameter is the cup-length $\ell\geq0$ and the other is the filtration parameter. This new persistence structure, called the persistent cup module, is induced by the cohomological cup product and adapted to the persistence setting. Furthermore, we show that this persi...
We develop persistent homology in the setting of filtered (Cech) closure spaces. Examples of filtere...
The use of persistent homology in applications is justified by the validity of certain stability res...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...
Cohomological ideas have recently been injected into persistent homology and have for example been u...
Persistent homology typically studies the evolution of homology groups Hp(X) (with coefficients in a...
The stability of persistent homology is rightly considered to be one of its most important propertie...
Persistent homology is a field within Topological Data Analysis that uses persistence modules to stu...
We define a class of invariants, which we call homological invariants, for persistence modules over ...
We define a class of multiparameter persistence modules that arise from a one-parameter family of fu...
Recently, it was found that there is a remarkable intuitive similarity between studies in theoretica...
Recently, it was found that there is a remarkable intuitive similarity between studies in theoretica...
We develop some aspects of the homological algebra of persistence modules, in both the one-parameter...
Multidimensional persistence studies topological features of shapes by analyzing the lower level set...
In persistent topology, q-tame modules appear as a natural and large class of persistence modules in...
The extended persistence diagram is an invariant of piecewise linear functions, introduced by Cohen-...
We develop persistent homology in the setting of filtered (Cech) closure spaces. Examples of filtere...
The use of persistent homology in applications is justified by the validity of certain stability res...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...
Cohomological ideas have recently been injected into persistent homology and have for example been u...
Persistent homology typically studies the evolution of homology groups Hp(X) (with coefficients in a...
The stability of persistent homology is rightly considered to be one of its most important propertie...
Persistent homology is a field within Topological Data Analysis that uses persistence modules to stu...
We define a class of invariants, which we call homological invariants, for persistence modules over ...
We define a class of multiparameter persistence modules that arise from a one-parameter family of fu...
Recently, it was found that there is a remarkable intuitive similarity between studies in theoretica...
Recently, it was found that there is a remarkable intuitive similarity between studies in theoretica...
We develop some aspects of the homological algebra of persistence modules, in both the one-parameter...
Multidimensional persistence studies topological features of shapes by analyzing the lower level set...
In persistent topology, q-tame modules appear as a natural and large class of persistence modules in...
The extended persistence diagram is an invariant of piecewise linear functions, introduced by Cohen-...
We develop persistent homology in the setting of filtered (Cech) closure spaces. Examples of filtere...
The use of persistent homology in applications is justified by the validity of certain stability res...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...