60 citations · 102 across the 3 of their papers we have counts for
3 papers
quant-ph2019★ 60 cited
Quantum Graph Neural Networks
Guillaume Verdon, Trevor McCourt, Enxhell Luzhnica +3
We introduce Quantum Graph Neural Networks (QGNN), a new class of quantum neural network ansatze which are tailored to represent quantum processes which have a graph structure, and…
cs.LG2019★ 11 cited
On Graph Classification Networks, Datasets and Baselines
Enxhell Luzhnica, Ben Day, Pietro Liò
Graph classification receives a great deal of attention from the non-Euclidean machine learning community. Recent advances in graph coarsening have enabled the training of deeper n…
cs.LG2019★ 31 cited
Clique pooling for graph classification
Enxhell Luzhnica, Ben Day, Pietro Lio'
We propose a novel graph pooling operation using cliques as the unit pool. As this approach is purely topological, rather than featural, it is more readily interpretable, a better…