Skip to content

Implementation of non-linear independent components estimation (NICE) in pytorch

License

Notifications You must be signed in to change notification settings

DakshIdnani/pytorch-nice

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PyTorch implementation of NICE

Original paper:

NICE: Non-linear Independent Components Estimation
Laurent Dinh, David Krueger, Yoshua Bengio

This implementation replicates the experiment on the MNIST dataset.

A test-set log likelihood of 1933.89 was recorded after 70 epochs with the current hyperparameters. The original paper reported a similar test-set log likelihood, 1980.50.

To train this on your own system, install NumPy and PyTorch, edit config.py, and run train.py.

Samples

About

Implementation of non-linear independent components estimation (NICE) in pytorch

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages