This document introduces a combinatorial theory of homology, a topological descriptor of shape. The past fifteen years have seen a steady advance in the use of techniques and principles from algebraic topology to address problems in the data sciences. This new subfield of Topological Data Analysis [TDA] seeks to extract robust qualitative features from large, noisy data sets. A primary tool in this new approach is the homological persistence module, which leverages the categorical structure of homological data to generate and relate shape descriptors across scales of measurement. We define a combinatorial analog to this structure in terms of matroid canonical forms. Our principle application is a novel algorithm to compute persistent homolo...
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has sh...
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has sh...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...
This document introduces a combinatorial theory of homology, a topological descriptor of shape. The ...
The topological data analysis studies the shape of a space at multiple scales. Its main tool is pers...
Persistent homology is a powerful notion rooted in topological data analysis which allows for retrie...
Abstract Persistent homology (PH) is a method used in topological data analysis (TDA) to study quali...
Summary. I develop algebraic-topological theories, algorithms and software for the analysis of non-l...
ABSTRACT. Persistent homology is an algebraic tool for measuring topological features of shapes and ...
Topological data analysis is a branch of computational topology which uses algebra to obtain topolo...
Persistent homology (PH) is a method used in topological data analysis (TDA) to study qualitative fe...
In algebraic topology it is well known that, using the Mayer\u2013Vietoris sequence, the homology of...
Taking images is an efficient way to collect data about the physical world. It can be done fast and ...
Topological data analysis (TDA) is a young field that has been rapidly growing over the last years ...
Abstract Persistent homology computes the multiscale topology of a data set by using a sequence of d...
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has sh...
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has sh...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...
This document introduces a combinatorial theory of homology, a topological descriptor of shape. The ...
The topological data analysis studies the shape of a space at multiple scales. Its main tool is pers...
Persistent homology is a powerful notion rooted in topological data analysis which allows for retrie...
Abstract Persistent homology (PH) is a method used in topological data analysis (TDA) to study quali...
Summary. I develop algebraic-topological theories, algorithms and software for the analysis of non-l...
ABSTRACT. Persistent homology is an algebraic tool for measuring topological features of shapes and ...
Topological data analysis is a branch of computational topology which uses algebra to obtain topolo...
Persistent homology (PH) is a method used in topological data analysis (TDA) to study qualitative fe...
In algebraic topology it is well known that, using the Mayer\u2013Vietoris sequence, the homology of...
Taking images is an efficient way to collect data about the physical world. It can be done fast and ...
Topological data analysis (TDA) is a young field that has been rapidly growing over the last years ...
Abstract Persistent homology computes the multiscale topology of a data set by using a sequence of d...
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has sh...
Topological data analysis (TDA) has been popularized since its development in early 2000. TDA has sh...
Harnessing the power of data has been a driving force for computing in recently years. However, the ...