# Fast approximate Bayesian inference for stable differential equation models

@article{Maybank2017FastAB, title={Fast approximate Bayesian inference for stable differential equation models}, author={Philip Maybank and Ingo Bojak and Richard G. Everitt}, journal={arXiv: Computation}, year={2017} }

Inference for mechanistic models is challenging because of nonlinear interactions between model parameters and a lack of identifiability. Here we focus on a specific class of mechanistic models, which we term stable differential equations. The dynamics in these models are approximately linear around a stable fixed point of the system. We exploit this property to develop fast approximate methods for posterior inference. We illustrate our approach using simulated data on a mechanistic…

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