Deep Gaussian processes and variational propagation of uncertainty
Uncertainty propagation across components of complex probabilistic models is vital for improving regularisation. Unfortunately, for many interesting models based on non-linear Gaussian processes (GPs), straightforward propagation of uncertainty is computationally and mathematically intractable. This...
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University of Sheffield
2015
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.665042 |