Machine learning for point clouds has been attracting much attention, wi...
Despite their successful application to a variety of tasks, neural netwo...
Counterfactual Explanation (CE) is a post-hoc explanation method that
pr...
Vanishing component analysis (VCA) computes approximate generators of
va...
The use of topological descriptors in modern machine learning applicatio...
In this article, we study curvature-like feature value of data sets in
E...
Although neural networks are capable of reaching astonishing performance...
Post-hoc explanation methods for machine learning models have been widel...
Solving optimization tasks based on functions and losses with a topologi...
Robust topological information commonly comes in the form of a set of
pe...
There are abundant cases for using Topological Data Analysis (TDA) in a
...
Persistence diagrams, the most common descriptors of Topological Data
An...
Persistence diagrams, a key descriptor from Topological Data Analysis, e...
Graph classification is a difficult problem that has drawn a lot of atte...
Despite strong stability properties, the persistent homology of filtrati...