  We introduce a method for solving the Max-Cut problem using a variational
algorithm and a continuous-variables quantum computing approach. The quantum
circuit consists of two parts: the first one embeds a graph into a circuit
using the Takagi decomposition and the second is a variational circuit which
solves the Max-Cut problem. We analyze how the presence of different types of
non-Gaussian gates influences the optimization process by performing numerical
simulations. We also propose how to treat the circuit as a machine learning
model.
