  This article aims to summarize recent and ongoing efforts to simulate
continuous-variable quantum systems using flow-based variational quantum Monte
Carlo techniques, focusing for pedagogical purposes on the example of bosons in
the field amplitude (quadrature) basis. Particular emphasis is placed on the
variational real- and imaginary-time evolution problems, carefully reviewing
the stochastic estimation of the time-dependent variational principles and
their relationship with information geometry. Some practical instructions are
provided to guide the implementation of a PyTorch code. The review is intended
to be accessible to researchers interested in machine learning and quantum
information science.
