Interpreting variational quantum models with active paths in parameterized quantum circuits
Variational quantum machine learning (VQML) models based on parameterized quantum circuits (PQC) have been expected to offer a potential quantum advantage for machine learning (ML) applications.However, comparison between VQML models and their 1861 remington revolver replica classical counterparts is hard due to the lack of interpretability of VQML