1 citations · 1 across the 2 of their papers we have counts for
3 papers
Quantum Graph Attention Networks: Trainable Quantum Encoders for Inductive Graph Learning
Arthur M. Faria, Mehdi Djellabi, Igor O. Sokolov +1
We introduce Quantum Graph Attention Networks (QGATs) as trainable quantum encoders for inductive learning on graphs, extending the Quantum Graph Neural Networks (QGNN) framework.…
Quantum Positional Encodings for Graph Neural Networks
Slimane Thabet, Mehdi Djellabi, Igor Sokolov +3
In this work, we propose novel families of positional encodings tailored to graph neural networks obtained with quantum computers. These encodings leverage the long-range correlati…
Enhancing Graph Neural Networks with Quantum Computed Encodings
Slimane Thabet, Romain Fouilland, Mehdi Djellabi +4
Transformers are increasingly employed for graph data, demonstrating competitive performance in diverse tasks. To incorporate graph information into these models, it is essential t…