Search Results for author: Andy Neely

Found 5 papers, 4 papers with code

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions

1 code implementation15 May 2019 Tim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely

A simple, flexible approach to creating expressive priors in Gaussian process (GP) models makes new kernels from a combination of basic kernels, e. g. summing a periodic and linear kernel can capture seasonal variation with a long term trend.

reinforcement-learning Reinforcement Learning (RL)

Bayesian Neural Network Ensembles

no code implementations27 Nov 2018 Tim Pearce, Mohamed Zaki, Andy Neely

Ensembles of neural networks (NNs) have long been used to estimate predictive uncertainty; a small number of NNs are trained from different initialisations and sometimes on differing versions of the dataset.

Uncertainty in Neural Networks: Approximately Bayesian Ensembling

2 code implementations12 Oct 2018 Tim Pearce, Felix Leibfried, Alexandra Brintrup, Mohamed Zaki, Andy Neely

Ensembling NNs provides an easily implementable, scalable method for uncertainty quantification, however, it has been criticised for not being Bayesian.

Bayesian Inference General Classification +2

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