Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization

2017/12/09 by McCarthy, Adam, Rodriguez, Blanca, Minchole, Ana
#FOS: Computer and information sciences #Machine Learning (stat.ML)

paper · doi:10.48550/arxiv.1712.03353

Abstract

Performing inference over simulators is generally intractable as their runtime means we cannot compute a marginal likelihood. We develop a likelihood-free inference method to infer parameters for a cardiac simulator, which replicates electrical flow through the heart to the body surface. We improve the fit of a state-of-the-art simulator to an electrocardiogram (ECG) recorded from a real patient.

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