477 citations · 1.4k across the 57 of their papers we have counts for
5 papers · 1 filter
A Meta-Learning Approach for Training Explainable Graph Neural Networks
Indro Spinelli, Simone Scardapane, Aurelio Uncini
In this paper, we investigate the degree of explainability of graph neural networks (GNNs). Existing explainers work by finding global/local subgraphs to explain a prediction, but…
Structured Ensembles: an Approach to Reduce the Memory Footprint of Ensemble Methods
Jary Pomponi, Simone Scardapane, Aurelio Uncini
In this paper, we propose a novel ensembling technique for deep neural networks, which is able to drastically reduce the required memory compared to alternative approaches. In part…
FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning
Indro Spinelli, Simone Scardapane, Amir Hussain +1
Graph representation learning has become a ubiquitous component in many scenarios, ranging from social network analysis to energy forecasting in smart grids. In several application…
A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling
Danilo Comminiello, Alireza Nezamdoust, Simone Scardapane +3
Nonlinear models are known to provide excellent performance in real-world applications that often operate in non-ideal conditions. However, such applications often require online p…
Avalanche: an End-to-End Library for Continual Learning
Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu +25
Learning continually from non-stationary data streams is a long-standing goal and a challenging problem in machine learning. Recently, we have witnessed a renewed and fast-growing…