  In this study, we provide error estimates and stability analysis of deep
learning techniques for certain partial differential equations including the
incompressible Navier-Stokes equations. In particular, we obtain explicit error
estimates (in suitable norms) for the solution computed by optimizing a loss
function in a Deep Neural Network (DNN) approximation of the solution, with a
fixed complexity.
