89 citations · 117 across the 8 of their papers we have counts for
3 papers · 1 filter
Evaluating Link Prediction Explanations for Graph Neural Networks
Claudio Borile, Alan Perotti, André Panisson
Graph Machine Learning (GML) has numerous applications, such as node/graph classification and link prediction, in real-world domains. Providing human-understandable explanations fo…
Beyond One-Hot-Encoding: Injecting Semantics to Drive Image Classifiers
Alan Perotti, Simone Bertolotto, Eliana Pastor +1
Images are loaded with semantic information that pertains to real-world ontologies: dog breeds share mammalian similarities, food pictures are often depicted in domestic environmen…
Streamlining models with explanations in the learning loop
Francesco Lomuscio, Paolo Bajardi, Alan Perotti +1
Several explainable AI methods allow a Machine Learning user to get insights on the classification process of a black-box model in the form of local linear explanations. With such…