A quantum boltzmann-variational autoencoder has shown improvement in deep learning. Research on this topic has been published in various outlets, including studies on the sample complexity of quantum boltzmann machine learning and the application of hybrid quantum-classical machine learning in chemistry and drug design. The technology appears to be related to quantum deep generative priors, energy-based models, and learning complex quantum distributions.