1 citations · 1 across the 2 of their papers we have counts for
3 papers
Boosting Relational Deep Learning with Pretrained Tabular Models
Veronica Lachi, Antonio Longa, Beatrice Bevilacqua +3
Relational databases, organized into tables connected by primary-foreign key relationships, are a common format for organizing data. Making predictions on relational data often inv…
TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphs
Yucheng Zhang, Beatrice Bevilacqua, Mikhail Galkin +1
Fully inductive knowledge graph models can be trained on multiple domains and subsequently perform zero-shot knowledge graph completion (KGC) in new unseen domains. This is an impo…
On the Effectiveness of Random Weights in Graph Neural Networks
Thu Bui, Carola-Bibiane Schönlieb, Bruno Ribeiro +2
Graph Neural Networks (GNNs) have achieved remarkable success across diverse tasks on graph-structured data, primarily through the use of learned weights in message passing layers.…