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https://github.com/brain-research/l2hmc

TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
https://github.com/brain-research/l2hmc

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TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network

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# L2HMC: Automatic Training of MCMC Samplers

TensorFlow open source implementation for training MCMC samplers from the paper:

[*Generalizing Hamiltonian Monte Carlo with Neural Networks*](https://arxiv.org/abs/1711.09268)

by [Daniel Levy](http://ai.stanford.edu/~danilevy), [Matt D. Hoffman](http://matthewdhoffman.com/) and [Jascha Sohl-Dickstein](sohldickstein.com)

---

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.

## Contact

***Code author:*** Daniel Levy

***Pull requests and issues:*** @daniellevy

## Citation

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}
}
```

## Note

This is not an official Google product.