vimco_tf

Variational Inference for Monte Carlo Objective (VIMCO) in tensorflow. The paper is here: https://arxiv.org/abs/1602.06725

This gets to a log-likelihood of -94.3 nats on the validation set of the binarized MNIST data.

How to run

Important: needs to be run with a tensorflow version of at least 0.11.0.

# get the binarized MNIST dataset, save to /tmp/binarized_mnist.hdf5
python make_binarized_mnist_hdf5_file.py

# run sbn training with vimco. ideally on GPU (10x speedup)
python sbn_vimco.py

#  visualize logs
tensorboard --logdir /tmp

Summaries and posterior predictives can be viewed on tensorboard:

This is heavily based off of Joost's implementation at https://github.com/y0ast/VIMCO (thank you Joost!)