Loading...

What are normalizing flows?

3,032 views

Loading...

Loading...

Transcript

The interactive transcript could not be loaded.

Loading...

Rating is available when the video has been rented.
This feature is not available right now. Please try again later.
Published on Dec 6, 2019

This short tutorial covers the basics of normalizing flows, a technique used in machine learning to build up complex probability distributions by transforming simple ones.

Papers to check out:
NICE: Non-linear Independent Components Estimation (https://arxiv.org/abs/1410.8516)
Density estimation using Real NVP (https://arxiv.org/abs/1605.08803)
Glow: Generative Flow with Invertible 1x1 Convolutions (https://arxiv.org/abs/1807.03039)
Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
Improving Variational Inference with Inverse Autoregressive Flow (https://arxiv.org/abs/1606.04934)
Masked Autoregressive Flow for Density Estimation (https://arxiv.org/abs/1705.07057)
MADE: Masked Autoencoder for Distribution Estimation (https://arxiv.org/abs/1502.03509)
Discrete Flows: Invertible Generative Models of Discrete Data (https://arxiv.org/abs/1905.10347)

Earlier work on flows:
A family of non-parametric density estimation algorithms (https://math.nyu.edu/faculty/tabak/pu...)

Additional reading:
https://deepgenerativemodels.github.i...
https://blog.evjang.com/2018/01/nf1.html
https://lilianweng.github.io/lil-log/...
http://akosiorek.github.io/ml/2018/04...

Special thanks to Alex Beatson, Geoffrey Roeder, Yaniv Ovadia, Sachin Ravi, and Ryan Adams for helpful feedback on this video.

Video style inspired by 3Blue1Brown (https://www.youtube.com/channel/UCYO_...)

Music: Trinkets by Vincent Rubinetti (https://vincerubinetti.bandcamp.com/t...)

Loading...

When autoplay is enabled, a suggested video will automatically play next.

Up next


to add this to Watch Later

Add to

Loading playlists...