activity
20232026
most citedLearning graphs and simplicial complexes from data

1 citations · 1 across the 8 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

eess.SP2024

Tracking Network Dynamics using Probabilistic State-Space Models

Victor M. Tenorio, Elvin Isufi, Geert Leus +1

This paper introduces a probabilistic approach for tracking the dynamics of unweighted and directed graphs using state-space models (SSMs). Unlike conventional topology inference m…

eess.SP2024

Polynomial Graphical Lasso: Learning Edges from Gaussian Graph-Stationary Signals

Andrei Buciulea, Jiaxi Ying, Antonio G. Marques +1

This paper introduces Polynomial Graphical Lasso (PGL), a new approach to learning graph structures from nodal signals. Our key contribution lies in modeling the signals as Gaussia…