no code implementations • 24 Oct 2023 • Matthew Ashman, Tommy Rochussen, Adrian Weller
The global inducing point variational approximation for BNNs is based on using a set of inducing inputs to construct a series of conditional distributions that accurately approximate the conditionals of the true posterior distribution.
1 code implementation • 6 Sep 2023 • Tommy Rochussen
Meta-learning is a framework in which machine learning models train over a set of datasets in order to produce predictions on new datasets at test time.