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 classical counterparts is hard due to the lack of interpretability of VQML models.In this study, we introd