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Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
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core init Apr 2, 2019
data
exp init Apr 2, 2019
figures add gif Apr 4, 2019
utils init Apr 2, 2019
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.gpflowrc init Apr 2, 2019
README.md minor Apr 4, 2019

README.md

Functional Variational Bayesian Neural Networks

This code is jointly contributed by Shengyang Sun, Guodong Zhang and Jiaxin Shi.

Introduction

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

Dependencies

This project runs with Python 3.6. Before running the code, you have to install

Experiments

Periodic Prior RBF Prior

Below we shows some examples to run the experiments.

x3 regression

python exp/toy.py -d x3 -in 0.01

sinusoidal extrapolation

python exp/toy.py -d sin -na 40 -nh 5 -nu 500 -e 50000 -il -2

Inference on Implicit Piecewise Priors

python exp/piecewise.py -d p_const

Contextual Bandits

python exp/bandits.py --data_type statlog

Citation

To cite this work, please use

@article{sun2019functional,
  title={Functional Variational Bayesian Neural Networks},
  author={Sun, Shengyang and Zhang, Guodong and Shi, Jiaxin and Grosse, Roger},
  journal={arXiv preprint arXiv:1903.05779},
  year={2019}
}
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