@book{rasmussen2006gaussian,
  title     = {{G}aussian processes for machine learning},
  author    = {Rasmussen, Carl Edward and Williams, Christopher K},
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}

@article{matthews2017gpflow,
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@inproceedings{abadi2016tensorflow,
  title={{TensorFlow}: A System for Large-Scale Machine Learning},
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  booktitle={12th {USENIX} symposium on operating systems design and implementation (OSDI 16)},
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  year={2016}
}


@article{gardner2018gpytorch,
  title={{Gpytorch}: Blackbox matrix-matrix gaussian process inference with {GPU} acceleration},
  author={Gardner, Jacob and Pleiss, Geoff and Weinberger, Kilian Q and Bindel, David and Wilson, Andrew G},
  journal={Advances in neural information processing systems},
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  year={2018}
}


@software{deepmind2020jax,
  title = {The {D}eep{M}ind {JAX} {E}cosystem},
  author = {Babuschkin, Igor and Baumli, Kate and Bell, Alison and Bhupatiraju, Surya and Bruce, Jake and Buchlovsky, Peter and Budden, David and Cai, Trevor and Clark, Aidan and Danihelka, Ivo and Fantacci, Claudio and Godwin, Jonathan and Jones, Chris and Hennigan, Tom and Hessel, Matteo and Kapturowski, Steven and Keck, Thomas and Kemaev, Iurii and King, Michael and Martens, Lena and Mikulik, Vladimir and Norman, Tamara and Quan, John and Papamakarios, George and Ring, Roman and Ruiz, Francisco and Sanchez, Alvaro and Schneider, Rosalia and Sezener, Eren and Spencer, Stephen and Srinivasan, Srivatsan and Stokowiec, Wojciech and Viola, Fabio},
  url = {http://github.com/deepmind},
  year = {2020},
}

@software{jax2018github,
  author = {James Bradbury and Roy Frostig and Peter Hawkins and Matthew James Johnson and Chris Leary and Dougal Maclaurin and George Necula and Adam Paszke and Jake Vander{P}las and Skye Wanderman-{M}ilne and Qiao Zhang},
  title = {{JAX}: composable transformations of {P}ython+{N}um{P}y programs},
  url = {http://github.com/google/jax},
  version = {0.2.5},
  year = {2018},
}


@article{fairbrother2022gaussianprocesses,
  title={{GaussianProcesses.jl}: A Nonparametric {Bayes} Package for the {Julia} Language},
  author={Fairbrother, Jamie and Nemeth, Christopher and Rischard, Maxime and Brea, Johanni and Pinder, Thomas},
  journal={Journal of Statistical Software},
  volume={102},
  pages={1--36},
  year={2022}
}

@article{pinder2022street,
  title={Street-Level Air Pollution Modelling with Graph {Gaussian} Processes},
  author={Pinder, Thomas and Turnbull, Kathryn and Nemeth, Christopher and Leslie, David},
  journal={ICLR: AI for Earth and Space Science},
  year={2022}
}

@article{pinder2021gaussian,
  title={{Gaussian} Processes on Hypergraphs},
  author={Pinder, Thomas and Turnbull, Kathryn and Nemeth, Christopher and Leslie, David},
  journal={arXiv preprint arXiv:2106.01982},
  year={2021}
}

@Misc{gpy2014,
  author =   {{GPy}},
  title =    {{GPy}: A {Gaussian} process framework in python},
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}

@Misc{blackjax2021,
  author =   {{BlackJax}},
  title =    {{BlackJAX}; a sampling library designed for ease of use, speed and modularity. },
  url = {https://github.com/blackjax-devs/blackjax/},
  year = {2021},
  publisher={Github},
  journal={Github repository},
}

@Misc{stheno2022tebbutt,
  title={{Stheno.jl.}},
  author = {Tebbutt W, Bruinsma W, Turner RE},
  url={https://github.com/JuliaGaussianProcesses/Stheno.jl},
  year = {2022},
  publisher={Github},
  journal={Github repository},
}

@article{rasmussen2010gaussian,
  title={{Gaussian} processes for machine learning ({GPML}) toolbox},
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  year={2010},
  publisher={JMLR. org}
}


@inproceedings{fajou20a,
  title = {Automated Augmented Conjugate Inference for Non-conjugate {Gaussian} Process Models},
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  booktitle = {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics},
  pages = {3025--3035},
  year = {2020},
  editor = {Silvia Chiappa and Roberto Calandra},
  volume = {108}, series = {Proceedings of Machine Learning Research},
  month = {26--28 Aug},
  publisher = {PMLR},
  pdf = {http://proceedings.mlr.press/v108/galy-fajou20a/galy-fajou20a.pdf},
  url = { http://proceedings.mlr.press/v108/galy-fajou20a.html },
}

@inproceedings{borovitskiy2021matern,
  title={Mat{\'e}rn {G}aussian processes on graphs},
  author={Borovitskiy, Viacheslav and Azangulov, Iskander and Terenin, Alexander and Mostowsky, Peter and Deisenroth, Marc and Durrande, Nicolas},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={2593--2601},
  year={2021},
  organization={PMLR}
}

@article{mallasto2017learning,
  title={Learning from uncertain curves: The 2-{W}asserstein metric for {G}aussian processes},
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  volume={30},
  year={2017}
}

@article{matheron1963principles,
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@article{mockus1978application,
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@inproceedings{deisenroth2011pilco,
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}
