https://github.com/WenboGong/MetaSGMCMC

The code for Meta Learning for SGMCMC
https://github.com/WenboGong/MetaSGMCMC

Last synced: 3 months ago
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The code for Meta Learning for SGMCMC

• Host: GitHub
• URL: https://github.com/WenboGong/MetaSGMCMC
• Owner: WenboGong
• Created: 2018-06-08T09:07:40.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-02-21T22:06:00.000Z (over 5 years ago)
• Last Synced: 2024-07-04T02:19:07.259Z (4 months ago)
• Language: Roff
• Size: 1.08 MB
• Stars: 24
• Watchers: 6
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Meta-Learning for Stochastic Gradient MCMC

This repo contains the implementation of the experiments in the following paper:

[Wenbo Gong*](http://mlg.eng.cam.ac.uk/?portfolio=wenbo-gong),

[Yingzhen Li*](http://yingzhenli.net) and

[Jose Miguel Hernandez Lobato](https://jmhl.org)

[Meta-Learning for Stochastic Gradient MCMC](https://openreview.net/forum?id=HkeoOo09YX)

International Conference on Learning Representations (ICLR), 2019

Contributions: Wenbo and Yingzhen initiated the project together. 

Wenbo designed thewith architecture of the sampler, and implemented all the experiments.

Yingzhen is mainly responsible for loss function design, experiment design, and the paper writing.

Miguel is here because he is Wenbo's PhD supervisor, and he provided some comments on the draft.

If you use our code in your research, please consider citing the paper.

## Gaussian experiments

See README in [Toy Example/](Toy%20Example/)

## MNIST experiments

See README in [BNN_MNIST/](BNN_MNIST/)

## Citing the paper (bib)

```

@inproceedings{

gong2018metalearning,

title={Meta-Learning For Stochastic Gradient {MCMC}},

author={Wenbo Gong and Yingzhen Li and José Miguel Hernández-Lobato},

booktitle={International Conference on Learning Representations},

year={2019},

url={https://openreview.net/forum?id=HkeoOo09YX},

}

```