Math insights for InfoGANs, VAEGANs, CycleGAN and more ( Generative adversarial networks papers )
Guys, here's my long-awaited mashup of 10 different GANs(Generative Adversarial Networks) papers with not soo cool rapping :p. The focus is on math intuition which is driving the paper. So enjoy and share it with your nerdy and not so nerdy friends.
Minor Mistake :
In CycleGANs, at 7 minute 20 second, the mapping needs to be reverse on right side.
Please consider supporting the channel on Patreon page :
/ crazymuse
Thanks to my current patrons for supporting the work :
1. Parth Parikh
2. Laher .D
3. Sean Marrett
-------------------------
The video covers :
1. InfoGANs • Math insights for InfoGANs, VAEGANs, Cycle...
2. Relativistic GANs • Math insights for InfoGANs, VAEGANs, Cycle...
3. CycleGANs • Math insights for InfoGANs, VAEGANs, Cycle...
4. SAGANs • Math insights for InfoGANs, VAEGANs, Cycle...
5. Progressive GANs • Math insights for InfoGANs, VAEGANs, Cycle...
6. DCGANs • Math insights for InfoGANs, VAEGANs, Cycle...
7. WGANs • Math insights for InfoGANs, VAEGANs, Cycle...
8. BEGANs • Math insights for InfoGANs, VAEGANs, Cycle...
9. VAEGANs • Math insights for InfoGANs, VAEGANs, Cycle...
10. Seq GANs • Math insights for InfoGANs, VAEGANs, Cycle...
For having two-sided live discussion, we also organize google hangouts on the meetup. You might wanna join it: https://www.meetup.com/crazymuse/
------------------------
Arxiv Links :
1. InfoGANs https://arxiv.org/abs/1606.03657
2. Relativistic GANs https://arxiv.org/abs/1807.00734
3. CycleGANs https://arxiv.org/abs/1703.10593
4. SAGANs https://arxiv.org/abs/1805.08318
5. Progressive GANs https://arxiv.org/abs/1710.10196
6. DCGANs https://arxiv.org/abs/1511.06434
7. WGANs https://arxiv.org/abs/1701.07875
8. BEGANs https://arxiv.org/abs/1703.10717
9. VAEGANs https://arxiv.org/abs/1512.09300
10. Seq GANs https://arxiv.org/abs/1609.05473
------------------------
Personal Anecdotes
Blogs by Marie, ( / decodyng ) inspire me to make relatable content. Her blogs make math intuitions in GANs look extremely simple without big terms. ( https://docs.google.com/document/d/1S... )
Blog by vincent ( https://vincentherrmann.github.io/blo... ) is a must read for people interested in math intuition behind WGANs.
Best youtube channel for understing ML is . . . Arxiv Insights. I love this channel a lot because it talks about math intuitions and digs deep into a topic, which is precicely what a researcher likes. Subscribe this channel too : / @arxivinsights
Cool then. So like every youtube, my parting words would be: subscribe the channel, press the bell icon and share the video :D
See ya next time homie :)