Code to go with the paper "Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo"

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Overview

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Code to go with the paper "Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo"

Requirements:

https://github.com/reml-lab/URSABench https://github.com/AdamCobb/hamiltorch

@article{kungurtsev2021decentralized,
  title={Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo},
  author={Kungurtsev, Vyacheslav and Cobb, Adam and Javidi, Tara and Jalaian, Brian},
  journal={arXiv preprint arXiv:2107.07211},
  year={2021}
}

Acknowledgements

VK was supported by the OP VVV project CZ.02.1.01/0.0/0.0/16_019/0000765 "Research Center for Informatics". Research reported in this paper was sponsored in part by the Army Research Laboratory under Cooperative Agreement W911NF-17-2-0196. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.

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