[enrmarc]

I read the paper, but I did not understand a thing. What is the path to follow (for example, books or papers to read) in order to at least understand what the paper is talking about? My background is in computer science.

[ttul]

Read the original GAN paper: https://arxiv.org/abs/1406.2661

[libdjml]

At what point did it go from understandable to not for you? Do you understand GAN architectures? Basic ideas of the DCGAN paper?

[johnwatson11218]

I did the Udacity nanodegree last year and the only part I never understood was the call to the "de-convolution" operator in tensorflow. It seems that every description keeps painting the same picture of how the two networks are in competition to reach "nash equilibrium". I think they really skimp over what a "de-convolution" actually is.

[libdjml]

Did you do the DLND? If so, they may have updated the videos, as the current explanation of conv2d_transpose seemed fairly clear to me. Or maybe it was some of the extra materials they provided that helped. I think I found a good video on YT also.

[johnwatson11218]

yea I did that program. I'll check it out again at some point and see if they added more description on that part of it.