A Laplacian-based Quantum Graph Neural Network for Semi-Supervised Learning

no code implementations • 10 Aug 2024 • Hamed Gholipour, Farid Bozorgnia, Kailash Hambarde, Hamzeh Mohammadigheymasi, Javier Mancilla, Andre Sequeira, Joao Neves, Hugo Proença

The performance of Laplacian learning is highly dependent on the number of entangling layers, with optimal configurations varying across different datasets.

Graph Neural Network

A Cluster-Based Opposition Differential Evolution Algorithm Boosted by a Local Search for ECG Signal Classification

no code implementations • 4 May 2023 • Mehran Pourvahab, Seyed Jalaleddin Mousavirad, Virginie Felizardo, Nuno Pombo, Henriques Zacarias, Hamzeh Mohammadigheymasi, Sebastião Pais, Seyed Nooreddin Jafari, Nuno M. Garcia

This paper employs an enhanced differential evolution (DE) algorithm for the training process as one of the most effective population-based algorithms.

Clustering