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.com/2012/04/05/viewing-computer-vision-from-a-bigger-picture/
https://computervisionblog.wordpress.com/2013/09/29/paper-talk-untangling-invariant-object-recognition/
https://prateekvjoshi.com/2014/06/21/what-is-manifold-learning/
https://medium.com/artists-and-machine-intelligence/a-journey-through-multiple-dimensions-and-transformations-in-space-the-final-frontier-d8435d81ca51
http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/
http://bjlkeng.github.io/posts/manifolds/
Lectures:
https://www.youtube.com/watch?v=oID20dIrV94&list=PLiPvV5TNogxKKwvKb1RKwkq2hm7ZvpHz0&index=2
https://www.youtube.com/watch?v=Yr1mOzC93xs
http://videolectures.net/mlss09us_niyogi_belkin_gmml/
http://videolectures.net/deeplearning2015_vincent_autoencoders/
Papers:
http://openaccess.thecvf.com/content_cvpr_2018_workshops/papers/w10/Shao_The_Riemannian_Geometry_CVPR_2018_paper.pdf
http://openscholarship.wustl.edu/cgi/viewcontent.cgi?article=1207&context=cse_research
https://arxiv.org/abs/1609.03552
http://www.lcayton.com/resexam.pdf
Videos and GAN implementations:
https://www.youtube.com/watch?v=QCSW4isBDL0
https://www.youtube.com/watch?v=YY6LrQSxIbc
https://www.youtube.com/watch?v=uoftpl3Bj6w
https://www.youtube.com/watch?v=4spmAO1JIfc
https://www.youtube.com/watch?v=2a3U4oHuvlE
__________________________________________________
Social Media:
Kartik Chincholikar Website: https://kartikchincholikar.github.io/
Github: https://github.com/kartikchincholikar
Twitter: https://twitter.com/KartikC14
_______________________________________________
I love coffee! Help fund future projects:
https://www.buymeacoffee.com/karti
_______________________________________________
Music:
Sérénade à Notre Dame de Paris by Amarià https://soundcloud.com/amariamusique
Creative Commons — Attribution 3.0 Unported — CC BY 3.0
Free Download / Stream: http://bit.ly/2vkP2eN
Music promoted by Audio Library https://youtu.be/HQH4vDELAFU
A New Year by Scott Buckley https://soundcloud.com/scottbuckley
Creative Commons — Attribution 3.0 Unported — CC BY 3.0
Free Download / Stream: https://bit.ly/_a-new-year
Music promoted by Audio Library https://youtu.be/FrLsadzQ2qc
I love coffee! Consider supporting:
https://www.buymeacoffee.com/karti