  In this paper, we introduce a prototype of machine learning method to solve
the many-body Schr\"{o}dinger equation by the tensor neural network. Based on
the tensor product structure, we can do the direct numerical integration by
using fixed quadrature points for the functions constructed by the tensor
neural network within tolerable computational complexity. The corresponding
machine learning method is built for solving many-body Schr\"{o}dinger
equation. Some numerical examples are provided to validate the accuracy and
efficiency of the proposed algorithms.
