"Amortised Inference" · 2 results · Global ETD Search

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Showing 1 to 2 of 2 for “"Amortised Inference"”.

Advances in approximate inference: combining VI and MCMC and improving on Stein discrepancy

Gong, WenboUniversity of Cambridge2021

… be able to reason under uncertainty. Bayesian inference, powered by the probabilistic framework, is believed to be a principled way to incorporate uncertainty into the decision making process. The difficulty of applying Bayesian inference in practice is rooted in the intractability of computing …

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Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning

Bauer, MatthiasUniversity of Cambridge2020

… models, and our ability to learn and make inferences from data. Specifically we present theoretical analyses alongside algorithmic and modelling advances in three areas of probabilistic machine learning: sparse Gaussian process approximations and invariant covariance functions, learning …

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