TensorFlow open source implementation for training MCMC samplers from the paper:
Generalizing Hamiltonian Monte Carlo with Neural Networks
by Daniel Levy, Matt D. Hoffman and Jascha Sohl-Dickstein
Given an analytically described distributions (implemented as in utils/distributions.py), L2HMC enables training of fast-mixing samplers. We provide an example, in the case of the Strongly-Correlated Gaussian, in the notebook SCGExperiment.ipynb --other details are included in the paper.
Code author: Daniel Levy
Pull requests and issues: @daniellevy
If you use this code, please cite our paper:
@article{levy2017generalizing,
title={Generalizing Hamiltonian Monte Carlo with Neural Networks},
author={Levy, Daniel and Hoffman, Matthew D. and Sohl-Dickstein, Jascha},
journal={International Conference on Learning Representations},
year={2018}
}
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