References

Here you can find links to the papers describing the algorithms implemented in Bensemble. We of course cannot leave the authors these algorithms uncredited.

• Practical variational inference - Alex Graves "Practical Variational Inference for Neural Networks" (2011)
• Kronecker-factored Laplace approximation - Hippolyt Ritter, Aleksandar Botev, David Barber "A Scalable Laplace Approximation for Neural Networks" (2018)
• Renyi divergence variational inference - Yingzhen Li, Richard E. Turner "Rényi Divergence Variational Inference" (2016)
• Probabilistic backpropagation - Jose Miguel Hernandez-Lobato, Ryan Adams "Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks" (2015)