Neural networks for inference, inference for neural networks

Thesis

Bayesian statistics is a powerful framework for modeling the world and reasoning over uncertainty. It provides a principled method for representing our prior knowledge, and updating that knowledge in the light of new information. Traditional Bayesian statistics, however, has been limited to simple models. Two of the main limiting factors for this are the expressiveness and flexibility of the probability distributions used, and the computational restrictions in performing inference and mode...

Expand abstract

Authors: Webb, S

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: variational autoencoders; variational inference; deep generative models; probabilistic programming
• Subjects: Bayesian Statistics; Deep Learning; Machine learning