70 citations · 118 across the 10 of their papers we have counts for
Showing 2022 · cs.LGShow all
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cs.LG2022★ 2 cited
Scalable Regularization of Scene Graph Generation Models using Symbolic Theories
Davide Buffelli, Efthymia Tsamoura
Several techniques have recently aimed to improve the performance of deep learning models for Scene Graph Generation (SGG) by incorporating background knowledge. State-of-the-art t…
cs.LG2022★ 12 cited
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks
Davide Buffelli, Pietro Liò, Fabio Vandin
In the past few years, graph neural networks (GNNs) have become the de facto model of choice for graph classification. While, from the theoretical viewpoint, most GNNs can operate…
cs.LG2022
Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach
Davide Buffelli, Fabio Vandin
Graph Neural Networks (GNNs) have become the state-of-the-art method for many applications on graph structured data. GNNs are a model for graph representation learning, which aims…