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cs.LG2023
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya
Elizaveta Semenova, Swapnil Mishra, Samir Bhatt +2
Model-based disease mapping remains a fundamental policy-informing tool in the fields of public health and disease surveillance. Hierarchical Bayesian models have emerged as the st…
stat.ML2023
PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling
Elizaveta Semenova, Prakhar Verma, Max Cairney-Leeming +3
Recent advances have shown that GP priors, or their finite realisations, can be encoded using deep generative models such as variational autoencoders (VAEs). These learned generato…