3 papers
eess.SP2024
Mitigating Subpopulation Bias for Fair Network Topology Inference
Madeline Navarro, Samuel Rey, Andrei Buciulea +2
We consider fair network topology inference from nodal observations. Real-world networks often exhibit biased connections based on sensitive nodal attributes. Hence, different subp…
eess.SP2023
Blind Deconvolution of Sparse Graph Signals in the Presence of Perturbations
Victor M. Tenorio, Samuel Rey, Antonio G. Marques
Blind deconvolution over graphs involves using (observed) output graph signals to obtain both the inputs (sources) as well as the filter that drives (models) the graph diffusion pr…
eess.SP2022
Enhanced graph-learning schemes driven by similar distributions of motifs
Samuel Rey, T. Mitchell Roddenberry, Santiago Segarra +1
This paper looks at the task of network topology inference, where the goal is to learn an unknown graph from nodal observations. One of the novelties of the approach put forth is t…