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paper.bib
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@misc{coullon2021efficient,
title={Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC},
author={Jeremie Coullon and Leah South and Christopher Nemeth},
year={2021},
eprint={2105.13059},
archivePrefix={arXiv},
primaryClass={stat.CO}
}
@article{nemeth2021stochastic,
title={{Stochastic gradient Markov chain Monte Carlo}},
author={Nemeth, Christopher and Fearnhead, Paul},
journal={Journal of the American Statistical Association},
volume={116},
number={533},
pages={433--450},
year={2021},
publisher={Taylor \& Francis}
}
@inproceedings{NIPS2015_Ma_complete_recipe,
author = {Ma, Yi-An and Chen, Tianqi and Fox, Emily},
booktitle = {Advances in Neural Information Processing Systems},
editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {A Complete Recipe for Stochastic Gradient MCMC},
url = {https://proceedings.neurips.cc/paper/2015/file/9a4400501febb2a95e79248486a5f6d3-Paper.pdf},
volume = {28},
year = {2015}
}
@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{baker2019sgmcmc,
title = {{sgmcmc}: An {R} Package for Stochastic Gradient {M}arkov chain {M}onte {C}arlo},
author = {Jack Baker and Paul Fearnhead and Emily B. Fox and Christopher Nemeth},
year = {2019},
month = {oct},
day = {31},
doi = {10.18637/jss.v091.i03},
volume = {91},
pages = {1--27},
journal = {Journal of Statistical Software},
issn = {1548-7660},
publisher = {University of California at Los Angeles},
number = {3},
}
@misc{tensorflow2015-whitepaper,
title={ {TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url={https://www.tensorflow.org/},
note={Software available from tensorflow.org},
author={
Mart\'{\i}n~Abadi and
Ashish~Agarwal and
Paul~Barham and
Eugene~Brevdo and
Zhifeng~Chen and
Craig~Citro and
Greg~S.~Corrado and
Andy~Davis and
Jeffrey~Dean and
Matthieu~Devin and
Sanjay~Ghemawat and
Ian~Goodfellow and
Andrew~Harp and
Geoffrey~Irving and
Michael~Isard and
Yangqing Jia and
Rafal~Jozefowicz and
Lukasz~Kaiser and
Manjunath~Kudlur and
Josh~Levenberg and
Dandelion~Man\'{e} and
Rajat~Monga and
Sherry~Moore and
Derek~Murray and
Chris~Olah and
Mike~Schuster and
Jonathon~Shlens and
Benoit~Steiner and
Ilya~Sutskever and
Kunal~Talwar and
Paul~Tucker and
Vincent~Vanhoucke and
Vijay~Vasudevan and
Fernanda~Vi\'{e}gas and
Oriol~Vinyals and
Pete~Warden and
Martin~Wattenberg and
Martin~Wicke and
Yuan~Yu and
Xiaoqiang~Zheng},
year={2015},
}
@Article{harris2020array,
title = {Array programming with {NumPy}},
author = {Charles R. Harris and K. Jarrod Millman and St{\'{e}}fan J.
van der Walt and Ralf Gommers and Pauli Virtanen and David
Cournapeau and Eric Wieser and Julian Taylor and Sebastian
Berg and Nathaniel J. Smith and Robert Kern and Matti Picus
and Stephan Hoyer and Marten H. van Kerkwijk and Matthew
Brett and Allan Haldane and Jaime Fern{\'{a}}ndez del
R{\'{i}}o and Mark Wiebe and Pearu Peterson and Pierre
G{\'{e}}rard-Marchant and Kevin Sheppard and Tyler Reddy and
Warren Weckesser and Hameer Abbasi and Christoph Gohlke and
Travis E. Oliphant},
year = {2020},
month = sep,
journal = {Nature},
volume = {585},
number = {7825},
pages = {357--362},
doi = {10.1038/s41586-020-2649-2},
publisher = {Springer Science and Business Media {LLC}},
url = {https://doi.org/10.1038/s41586-020-2649-2}
}
@unpublished{murphy2023 ,
title={Probabilistic Machine Learning: Advanced Topics},
author={Kevin Murphy},
year={2023},
url = {https://probml.github.io/pml-book/book2.html},
note = "In preparation",
}