I'm interested in using GAN as a method to make authorship attribution more robust.

Using complex NN models (let's say, LSTM) doesn't give much better results than simple neurons with deep layers. Seems that the model extraction (how to represent some author style) is the only point that matters, and it then easily forged (i.e., not hard to reproduce the desired style on purpose).

I'm trying to use GAN as a mean of desconstruction, of removal of the ease patterns to see if some NN can use subtle characteristics to identify the author.