activity
20242026
collaborators

6 papers

stat.ML2026

Conic Formulations of Transport Metrics for Unbalanced Measure Networks and Hypernetworks

Mary Chriselda Antony Oliver, Emmanuel Hartman, Tom Needham

The Gromov-Wasserstein (GW) variant of optimal transport, designed to compare probability densities defined over distinct metric spaces, has emerged as an important tool for the an…

math.AT2025

Persistent Homology for Labeled Datasets: Gromov-Hausdorff Stability and Generalized Landscapes

Yaoying Fu, Evgeniya Lagoda, Shiying Li +3

Techniques from metric geometry have become fundamental tools in modern mathematical data science, providing principled methods for comparing datasets modeled as finite metric spac…

stat.ML2025

Metrics for Parametric Families of Networks

Mario Gómez, Guanqun Ma, Tom Needham +1

We introduce a general framework for analyzing data modeled as parameterized families of networks. Building on a Gromov-Wasserstein variant of optimal transport, we define a family…

math.AT2025

Topological Optimal Transport for Geometric Cycle Matching

Stephen Y Zhang, Michael P H Stumpf, Tom Needham +1

Topological data analysis is a powerful tool for describing topological signatures in real world data. An important challenge in topological data analysis is matching significant t…

math.MG2024

Geometry of the Space of Partitioned Networks: A Unified Theoretical and Computational Framework

Stephen Y Zhang, Fangfei Lan, Youjia Zhou +4

Interactions and relations between objects may be pairwise or higher-order in nature, and so network-valued data are ubiquitous in the real world. The "space of networks", however,…

math.MG2024

Stability of Hypergraph Invariants and Transformations

Tom Needham, Ethan Semrad

Graphs are fundamental tools for modeling pairwise interactions in complex systems. However, many real-world systems involve multi-way interactions that cannot be fully captured by…