70 citations · 118 across the 10 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 16 cited
A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings
Davide Buffelli, Fabio Vandin
Graph Neural Networks (GNNs) are a framework for graph representation learning, where a model learns to generate low dimensional node embeddings that encapsulate structural and fea…
cs.LG2020★ 70 cited
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation
Davide Buffelli, Fabio Vandin
Sensor-based human activity recognition (HAR) requires to predict the action of a person based on sensor-generated time series data. HAR has attracted major interest in the past fe…
cs.LG2020★ 8 cited
The Impact of Global Structural Information in Graph Neural Networks Applications
Davide Buffelli, Fabio Vandin
Graph Neural Networks (GNNs) rely on the graph structure to define an aggregation strategy where each node updates its representation by combining information from its neighbours.…