  In this article, we propose the fractional weak adversarial networks (f-WANs)
for the stationary fractional advection dispersion equations (FADE) based on
their weak formulas. This enables us to handle less regular solutions for the
fractional equations. To handle the non-local property of the fractional
derivatives, convolutional layers and special loss functions are introduced in
this neural network. Numerical experiments for both smooth and less regular
solutions show the validity of f-WANs.
