Published in Submitted to Quantum Machine Intelligence, 2020
Generative Modelling has become a promising use case for near term quantum computers. In particular, due to the fundamentally probabilistic nature of quantum mechanics, quantum computers naturally model and learn probability distributions. The Born machine is an example of such a model. Here we present the Born machine within the framework of Continuous Variable Quantum Computing for the purpose of learning continuous probability distributions.