3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
Sparse Vicious Attacks on Graph Neural Networks
Giovanni Trappolini, Valentino Maiorca, Silvio Severino +3
Graph Neural Networks (GNNs) have proven to be successful in several predictive modeling tasks for graph-structured data. Amongst those tasks, link prediction is one of the fundame…
Explanatory Learning: Beyond Empiricism in Neural Networks
Antonio Norelli, Giorgio Mariani, Luca Moschella +4
We introduce Explanatory Learning (EL), a framework to let machines use existing knowledge buried in symbolic sequences -- e.g. explanations written in hieroglyphic -- by autonomou…
Universal Spectral Adversarial Attacks for Deformable Shapes
Arianna Rampini, Franco Pestarini, Luca Cosmo +2
Machine learning models are known to be vulnerable to adversarial attacks, namely perturbations of the data that lead to wrong predictions despite being imperceptible. However, the…
Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi +1
We propose a novel approach to disentangle the generative factors of variation underlying a given set of observations. Our method builds upon the idea that the (unknown) low-dimens…