On a dataset of 80 epitopes, a high-entanglement ZZ feature map in a hybrid QNN showed lower training AUAC and higher test-to-training AUAC ratio than lower-entanglement maps while keeping competitive test accuracy.
Hybrid Quantum Neural Networks for EXicient Protein-Ligand Binding AXinity Prediction
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Exploring the Effects of Entanglement on Quantum Machine Learning of Pathogen Epitope-Receptor Binding
On a dataset of 80 epitopes, a high-entanglement ZZ feature map in a hybrid QNN showed lower training AUAC and higher test-to-training AUAC ratio than lower-entanglement maps while keeping competitive test accuracy.