Generative Adversarial Networks - FUTURISTIC & FUN AI !
I talk about Generative Adversarial Networks, how it works, fun applications and it’s types. If you liked the video, click that like button and SUBSCIBE for more content on Data Sciences, Machine Learning & Deep Learning.
Follow me on QUORA for my answers to interesting questions on Data Sciences, Machine Learning, Programming & AI: https://www.quora.com/profile/Ajay-Halthor
Music at: https://www.bensound.com/royalty-free-music/track/tenderness
LINKS TO INTERESTING APPLICATIONS
Progressive Growing of GANs for Improved Quality, Stability, and Variation: https://www.youtube.com/watch?v=XOxxPcy5Gr4
Pix2Pix: https://affinelayer.com/pixsrv/
Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs: https://arxiv.org/pdf/1801.00077.pdf
LINKS TO PAPERS & BLOG POSTS
Good Introduction to GANs: https://robotronblog.com/2017/09/05/gans/
Detailed overview of GANs & Types: http://guimperarnau.com/blog/2017/03/Fantastic-GANs-and-where-to-find-them#wassGANs
About the loss function: https://danieltakeshi.github.io/2017/03/05/understanding-generative-adversarial-networks/
Deep Convolutional GANs: https://arxiv.org/pdf/1511.06434.pdf
Deconvolutional Networks: http://www.matthewzeiler.com/wp-content/uploads/2017/07/cvpr2010.pdf
Conditional GANs: : https://arxiv.org/pdf/1411.1784.pdf
InfoGAN: https://arxiv.org/abs/1606.03657
More Accessable blog: http://aiden.nibali.org/blog/2016-12-01-implementing-infogan/
Wasserstein GANs (original paper): https://arxiv.org/pdf/1701.07875.pdf
Accessible blog : https://www.alexirpan.com/2017/02/22/wasserstein-gan.html
Text to Image Synthesis with StackGAN: https://arxiv.org/pdf/1612.03242.pdf
Видео Generative Adversarial Networks - FUTURISTIC & FUN AI ! канала CodeEmporium
Follow me on QUORA for my answers to interesting questions on Data Sciences, Machine Learning, Programming & AI: https://www.quora.com/profile/Ajay-Halthor
Music at: https://www.bensound.com/royalty-free-music/track/tenderness
LINKS TO INTERESTING APPLICATIONS
Progressive Growing of GANs for Improved Quality, Stability, and Variation: https://www.youtube.com/watch?v=XOxxPcy5Gr4
Pix2Pix: https://affinelayer.com/pixsrv/
Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs: https://arxiv.org/pdf/1801.00077.pdf
LINKS TO PAPERS & BLOG POSTS
Good Introduction to GANs: https://robotronblog.com/2017/09/05/gans/
Detailed overview of GANs & Types: http://guimperarnau.com/blog/2017/03/Fantastic-GANs-and-where-to-find-them#wassGANs
About the loss function: https://danieltakeshi.github.io/2017/03/05/understanding-generative-adversarial-networks/
Deep Convolutional GANs: https://arxiv.org/pdf/1511.06434.pdf
Deconvolutional Networks: http://www.matthewzeiler.com/wp-content/uploads/2017/07/cvpr2010.pdf
Conditional GANs: : https://arxiv.org/pdf/1411.1784.pdf
InfoGAN: https://arxiv.org/abs/1606.03657
More Accessable blog: http://aiden.nibali.org/blog/2016-12-01-implementing-infogan/
Wasserstein GANs (original paper): https://arxiv.org/pdf/1701.07875.pdf
Accessible blog : https://www.alexirpan.com/2017/02/22/wasserstein-gan.html
Text to Image Synthesis with StackGAN: https://arxiv.org/pdf/1612.03242.pdf
Видео Generative Adversarial Networks - FUTURISTIC & FUN AI ! канала CodeEmporium
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