This repository contains the code for the Quantum Variational Autoencoder (QVAE) model, which is a quantum generative model that can be used to generate quantum states. The QVAE model is based on the Variational Autoencoder (VAE) model, which is a generative model that can be used to generate classical data. The QVAE model is designed to generate quantum states that are close to a target quantum state, and it does this by learning a low-dimensional representation of the target quantum state and then using this representation to generate new quantum states that are similar to the target state.
vqc.py: variational quantum autoencoder for MNIST datasetvqc-mols.py: variational quantum autoencoder for molecular dataset