Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326

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Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326 |

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Readme

This code is jointly contributed by Shengyang Sun, Guodong Zhang, Chaoqi Wang and Wenyuan Zeng

Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" (https://arxiv.org/abs/1806.04326)

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

Below we shows some examples to run the experiments. We also provide experiment figures and logging files in results folder, as a reference.

```
python exp/time-series.py --name airline --kern nkn
```

```
python exp/regression.py --data energy --split uci_woval --kern nkn
python exp/regression.py --data energy --split uci_woval_pca --kern nkn
```

```
python exp/bayes-opt.py --name sty --kern nkn --run 0
```

```
python exp/texture.py --data pave --kern nkn
```

To cite this work, please use

```
@article{sun2018differentiable,
title={Differentiable Compositional Kernel Learning for Gaussian Processes},
author={Sun, Shengyang and Zhang, Guodong and Wang, Chaoqi and Zeng, Wenyuan and Li, Jiaman and Grosse, Roger},
journal={arXiv preprint arXiv:1806.04326},
year={2018}
}
```

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