• Corpus ID: 233210565

GPflux: A Library for Deep Gaussian Processes

@article{Dutordoir2021GPfluxAL,
  title={GPflux: A Library for Deep Gaussian Processes},
  author={Vincent Dutordoir and Hugh Salimbeni and Eric Hambro and John Mcleod and Felix Leibfried and Artem Artemev and Mark van der Wilk and James Hensman and Marc Peter Deisenroth and S. T. John},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.05674}
}
We introduce GPflux, a Python library for Bayesian deep learning with a strong emphasis on deep Gaussian processes (DGPs). Implementing DGPs is a challenging endeavour due to the various mathematical subtleties that arise when dealing with multivariate Gaussian distributions and the complex bookkeeping of indices. To date, there are no actively maintained, open-sourced and extendable libraries available that support research activities in this area. GPflux aims to fill this gap by providing a… 
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