In recent years the statistical analysis of topological signatures computable from a possibly high-dimensional point cloud has attracted increasing attention from a theoretical as well as applied point of view. In this work we briefly review the basic techniques and main inferential results available in the TDA (Topological Data Analysis) toolkit, showing them in action on two classification problems related to activity tracking tasks
Thesis (Ph.D.)--University of Washington, 2020Many real-world data sets can be viewed as a noisy sam...
Human motion analysis is a very important research topic in the field of computer vision, as evidenc...
International audienceIt has been observed since a long time that data are often carrying interestin...
Abstract Propelled by a fast evolving landscape of techniques and datasets, data science is growing ...
Topological Data Analysis (TDA), which refers to methods of utilizing topological features in data (...
Topological data analysis (TDA) is an approach to the analysis of datasets using techniques from top...
Topological Data Analysis is an emerging field at the intersection of algebraic topology and statist...
Topological Data Analysis (TDA) combines topology and data analytics which offers a new perspective ...
Multidimensional sensors represent an increasingly popular, yet challenging data source in modern st...
The last decade saw an enormous boost in the field of computational topology: methods and concepts f...
Topological data analysis computes and analyses topological features of the point clouds by construc...
This paper works as a motivation to consider stronger methods in TDA (Topological Data Analysis). We...
This dissertation presents novel approaches and applications of machine learning architectures. In p...
Topological Data Analysis (TDA) is a novel statistical technique, particularly powerful for the anal...
International audienceThis tutorial presents topological methods for the analysis and visualization ...
Thesis (Ph.D.)--University of Washington, 2020Many real-world data sets can be viewed as a noisy sam...
Human motion analysis is a very important research topic in the field of computer vision, as evidenc...
International audienceIt has been observed since a long time that data are often carrying interestin...
Abstract Propelled by a fast evolving landscape of techniques and datasets, data science is growing ...
Topological Data Analysis (TDA), which refers to methods of utilizing topological features in data (...
Topological data analysis (TDA) is an approach to the analysis of datasets using techniques from top...
Topological Data Analysis is an emerging field at the intersection of algebraic topology and statist...
Topological Data Analysis (TDA) combines topology and data analytics which offers a new perspective ...
Multidimensional sensors represent an increasingly popular, yet challenging data source in modern st...
The last decade saw an enormous boost in the field of computational topology: methods and concepts f...
Topological data analysis computes and analyses topological features of the point clouds by construc...
This paper works as a motivation to consider stronger methods in TDA (Topological Data Analysis). We...
This dissertation presents novel approaches and applications of machine learning architectures. In p...
Topological Data Analysis (TDA) is a novel statistical technique, particularly powerful for the anal...
International audienceThis tutorial presents topological methods for the analysis and visualization ...
Thesis (Ph.D.)--University of Washington, 2020Many real-world data sets can be viewed as a noisy sam...
Human motion analysis is a very important research topic in the field of computer vision, as evidenc...
International audienceIt has been observed since a long time that data are often carrying interestin...