My Understanding of the Manifold Hypothesis ft Geoffrey Hinton | Deep Learning

Автор: Kartik Chincholikar

Загружено: 2020-03-30

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Описание: If you think I've misunderstood something, please let me know in the comments!

Below is the mash up of quotes which motivate this video:
Real datasets actually contain a tremendous amount of structure, or else we could not learn from them. The manifold hypothesis is that real life high-dimensional data of interest often
lives in an unknown lower-dimensional manifold embedded in ambient space.
it is only slightly overstating the case to say that physics is the study of symmetry.

Below are all the blogs/papers/videos I've referred to:

Blogs:

https://en.wikipedia.org/wiki/Hypercube

https://computervisionblog.wordpress....

https://computervisionblog.wordpress....

https://prateekvjoshi.com/2014/06/21/...

  / a-journey-through-multiple-dimensions-and-...

http://colah.github.io/posts/2014-03-...

http://bjlkeng.github.io/posts/manifo...

Lectures:
   • Lecture 2/16 : The Perceptron learning pro...

   • From Deep Learning of Disentangled Represe...
http://videolectures.net/mlss09us_niy...
http://videolectures.net/deeplearning...

Papers:

http://openaccess.thecvf.com/content_...

http://openscholarship.wustl.edu/cgi/...

https://arxiv.org/abs/1609.03552

http://www.lcayton.com/resexam.pdf

Videos and GAN implementations:
   • Chairs morphing
   • The 1000 ImageNet Categories inside of BigGAN
   • InterFaceGAN Demo (CVPR 2020)
   • Видео
   • Stylegan on Anime Girls

__________________________________________________
Social Media:
Kartik Chincholikar Website: https://kartikchincholikar.github.io/
Github: https://github.com/kartikchincholikar
Twitter:   / kartikc14
_______________________________________________
I love coffee! Help fund future projects:
https://www.buymeacoffee.com/karti
_______________________________________________

Music:

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My Understanding of the Manifold Hypothesis ft Geoffrey Hinton | Deep Learning

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