> For the complete documentation index, see [llms.txt](https://stephanosterburg.gitbook.io/scrapbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://stephanosterburg.gitbook.io/scrapbook/3deeplearning/fast-and-deep-deformation-approximations.md).

# Fast and Deep Deformation Approximations

{% embed url="<https://youtu.be/NKjfdR2fmVs>" %}

The SIGGRAPH series is here. You have cast your votes, now I’m publishing four short videos (and support material) on the papers you have found most interesting. I’ll publish this videos bi-weekly. The first one is on the paper [‘Fast and Deep Deformation Approximations’](http://graphics.berkeley.edu/papers/Bailey-FDD-2018-08/index.html) by Bailey et al. Hope you like this!

I’ve also created a prototype implementation of this paper for you, [check it out!](/scrapbook/3deeplearning/fast-and-deep-deformation-approximations.md)

Links mentioned in the video:

[Link to the original paper](http://graphics.berkeley.edu/papers/Bailey-FDD-2018-08/index.html)

**7’10”**

* [How Neural Networks work (Article)](https://3deeplearner.org/what-is-nn)
* [How to train a Neural Network and use it in Maya (How to Tutorial)](https://3deeplearner.org/neural-network-inside-maya)
* [How to use Neural Networks in Maya interactively (How to Tutorial)](https://3deeplearner.org/neuralnet-python-dg-node)

**19’30”**

* [Implementing Fast and Deep Deformation Approximations in Maya (Prototype tutorial)](https://3deeplearner.org/fdda-implementation)<br>