1 citations · 1 across the 11 of their papers we have counts for
3 papers · 1 filter
Robust Graph Neural Network based on Graph Denoising
Victor M. Tenorio, Samuel Rey, Antonio G. Marques
Graph Neural Networks (GNNs) have emerged as a notorious alternative to address learning problems dealing with non-Euclidean datasets. However, although most works assume that the…
Recovering Missing Node Features with Local Structure-based Embeddings
Victor M. Tenorio, Madeline Navarro, Santiago Segarra +1
Node features bolster graph-based learning when exploited jointly with network structure. However, a lack of nodal attributes is prevalent in graph data. We present a framework to…
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…