49 citations · 144 across the 24 of their papers we have counts for
4 papers · 2 filters
GNNs Meet Sequence Models Along the Shortest-Path: an Expressive Method for Link Prediction
Francesco Ferrini, Veronica Lachi, Antonio Longa +2
Graph Neural Networks (GNNs) often struggle to capture the link-specific structural patterns crucial for accurate link prediction, as their node-centric message-passing schemes ove…
Bridging Theory and Practice in Link Representation with Graph Neural Networks
Veronica Lachi, Francesco Ferrini, Antonio Longa +3
Graph Neural Networks (GNNs) are widely used to compute representations of node pairs for downstream tasks such as link prediction. Yet, theoretical understanding of their expressi…
A Benchmark Dataset for Graph Regression with Homogeneous and Multi-Relational Variants
Peter Samoaa, Marcus Vukojevic, Morteza Haghir Chehreghani +1
Graph-level regression underpins many real-world applications, yet public benchmarks remain heavily skewed toward molecular graphs and citation networks. This limited diversity hin…
Simple Path Structural Encoding for Graph Transformers
Louis Airale, Antonio Longa, Mattia Rigon +2
Graph transformers extend global self-attention to graph-structured data, achieving notable success in graph learning. Recently, random walk structural encoding (RWSE) has been fou…