179 citations · 306 across the 11 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.LG2021★ 8 cited
On the approximation capability of GNNs in node classification/regression tasks
Giuseppe Alessio D'Inverno, Monica Bianchini, Maria Lucia Sampoli +1
Graph Neural Networks (GNNs) are a broad class of connectionist models for graph processing. Recent studies have shown that GNNs can approximate any function on graphs, modulo the…
eess.IV2021★ 4 cited
A multi-stage GAN for multi-organ chest X-ray image generation and segmentation
Giorgio Ciano, Paolo Andreini, Tommaso Mazzierli +2
Multi-organ segmentation of X-ray images is of fundamental importance for computer aided diagnosis systems. However, the most advanced semantic segmentation methods rely on deep le…