The importance of being correlated: Implications of dependence in joint spectral inference across multiple networks

K Pantazis, A Athreya, J Arroyo, WN Frost… - Journal of Machine …, 2022 - jmlr.org
Spectral inference on multiple networks is a rapidly-develo** subfield of graph statistics.
Recent work has demonstrated that joint, or simultaneous, spectral embedding of multiple …

Matchability of heterogeneous networks pairs

V Lyzinski, DL Sussman - Information and Inference: A Journal of …, 2020 - academic.oup.com
We consider the problem of graph matchability in non-identically distributed networks. In a
general class of edge-independent networks, we demonstrate that graph matchability can …

Maximum likelihood estimation and graph matching in errorfully observed networks

J Arroyo, DL Sussman, CE Priebe… - … of Computational and …, 2021 - Taylor & Francis
Given a pair of graphs with the same number of vertices, the inexact graph matching
problem consists in finding a correspondence between the vertices of these graphs that …

Statistical Modeling and Inference for Populations of Networks and Longitudinal Data

C Mantoux - 2022 - theses.hal.science
The development and massification of medical imaging and clinical followup databases
open up new perspectives for understanding complex phenomena such as ageing or …

Statistical Inference across Multiple Networks: Advancements in Multiplex Graph Matching and Joint Spectral Network Embeddings

K Pantazis - 2022 - search.proquest.com
Networks are commonly used to model and study complex systems that arise in a variety of
scientific domains. One important network data modality is multiplex networks which are …

[PDF][PDF] Modelisation statistique et inference pour les populations de reseaux de connectivitecerebrale et les donnees longitudinales

CLE MANTOUX - 2022 - cmantoux.github.io
Résumé Le développement et la massification des bases de données d'imagerie médicale
et de suivi clinique ouvrent de nouvelles perspectives pour la compréhension de …