  We introduce the Neural Approximated Virtual Element Method, a novel
polygonal method that relies on neural networks to eliminate the need for
projection and stabilization operators in the Virtual Element Method. In this
paper, we discuss its formulation and detail the strategy for training the
underlying neural network. The efficacy of this new method is tested through
numerical experiments on elliptic problems.
