/pytorch-nice

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

Primary LanguagePythonMIT LicenseMIT

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