Learning to Program Adaptive Non-Local Observables for Machine Learning
This work proposes QFWP-ANO, a novel architecture which employs a classical hypernetwork to dynamically program VQC parameters and/or non-local observables conditioned on each input, and establishes input-conditioned ANO as an effective approach for enhancing QNNs.
Yu-Ting Lee, Samuel Yen-Chi Chen, Huan-Hsin Tseng
· 0 citations