Fun project, even though I personally find the gan images unconvincing; too many deconvolution artifacts, and poor conservation of mass as another commenter sai

Fun project, even though I personally find the gan images unconvincing; too many deconvolution artifacts, and poor conservation of mass as another commenter said. I am however completely awed by the folder in that git repo with 143.000 png files. Checking that into git would have turned my laptop itself into a molten blob of wax, haha. Edit: rereading my comment, maybe it sounds harsh. Idon't wanna sound like I'm dissing this, GANs are hard and so is image generation. I couldn't have done it better. Also: nice trick on penalizing poor (growing) noise vectors; another thing you could try is simply always sample a random point on an n-sphere (you divide your random vector by its length, it'll always have length 1)