5 papers
Building confidence regions for Reeb graphs using the interleaving distance
Matteo Pegoraro, Alberto Conforti, Mathieu Carrière
We develop confidence regions for Reeb graphs from finite samples using the interleaving distance. Given a point cloud equipped with a filter function, we construct a finite proxim…
TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
Matteo Biagetti, Mathieu Carrière, Francesco Conti +3
Persistence diagrams provide stable, interpretable summaries of geometric and topological structure and are useful for simulation-based inference when low-order statistics miss key…
Persistence-based topological optimization: a survey
Mathieu Carriere, Yuichi Ike, Théo Lacombe +1
Computational topology provides a tool, persistent homology, to extract quantitative descriptors from structured objects (images, graphs, point clouds, etc). These descriptors can…
Ultrafast topological data analysis reveals pandemic-scale dynamics of convergent evolution
Michael Bleher, Lukas Hahn, Maximilian Neumann +6
Genome variants which re-occur independently across evolutionary lineages are key molecular signatures of adaptation. Inferring the dynamics of such genetic changes from pandemic-s…
Multi-parameter Module Approximation: an efficient and interpretable invariant for multi-parameter persistence modules with guarantees
David Loiseaux, Mathieu Carrière, Andrew J. Blumberg
In this article, we introduce a new parameterized family of topological descriptors, taking the form of candidate decompositions, for multi-parameter persistence modules, and we id…