4 papers
Learning Product Graphs from Two-dimensional Stationary Signals
Andrei Buciulea, Bishwadeep Das, Elvin Isufi +1
Graph learning aims to infer a network structure directly from observed data, enabling the analysis of complex dependencies in irregular domains. Traditional methods focus on scala…
Graph signal aware decomposition of dynamic networks via latent graphs
Bishwadeep Das, Andrei Buciulea, Antonio G. Marques +1
Dynamics on and of networks refer to changes in topology and node-associated signals, respectively and are pervasive in many socio-technological systems, including social, biologic…
Matched Topological Subspace Detector
Chengen Liu, Victor M. Tenorio, Antonio G. Marques +1
Topological spaces, represented by simplicial complexes, capture richer relationships than graphs by modeling interactions not only between nodes but also among higher-order entiti…
Learning the Topology of a Simplicial Complex Using Simplicial Signals: A Greedy Approach
A. Buciulea, E. Isufi, G. Leus +1
Graphs are ubiquitous to model the irregular (non-Euclidean) structure of complex data, but they are limited to pairwise relationships and fail to model the complexities of the dat…