Researchers are exploring compositional approaches to build larger quantum models from smaller, trainable subcomponents—improving max-clique detection in quantum machine learning.
Quantum graph networks find larger cliques with less training
Researchers are exploring compositional approaches to build larger quantum models from smaller, trainable subcomponents—improving max-clique detection in quantum machine learning.