72 citations · 74 across the 5 of their papers we have counts for
4 papers · 1 filter
Explaining Graph Neural Networks for Node Similarity on Graphs
Daniel Daza, Cuong Xuan Chu, Trung-Kien Tran +3
Similarity search is a fundamental task for exploiting information in various applications dealing with graph data, such as citation networks or knowledge graphs. While this task h…
Discovering Association Rules in High-Dimensional Small Tabular Data
Erkan Karabulut, Daniel Daza, Paul Groth +1
Association Rule Mining (ARM) aims to discover patterns between features in datasets in the form of propositional rules, supporting both knowledge discovery and interpretable machi…
GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks
Taraneh Younesian, Daniel Daza, Emile van Krieken +2
Graph neural networks (GNNs) learn to represent nodes by aggregating information from their neighbors. As GNNs increase in depth, their receptive field grows exponentially, leading…
A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs
Tamara Cucumides, Daniel Daza, Pablo Barceló +4
The challenge of answering graph queries over incomplete knowledge graphs is gaining significant attention in the machine learning community. Neuro-symbolic models have emerged as…