Automatic Bayesian Inference of Reaction Networks via Guiding
Jump process models based on chemical reaction networks are ubiquitous, especially in systems biology modeling. However, performing inference on the latent variables and parameters of such models is challenging, particularly when the observations of the system state are noisy and incomplete. This th...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/157193 |