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Variational inference for Markov jump processes
Manfred Opper · Guido Sanguinetti

Tue Dec 04 10:30 AM -- 10:40 AM (PST) @ None #None

Markov jump processes play an important role in a large number of application domains. However, realistic systems are analytically intractable and they have traditionally been analysed using simulation based techniques, which do not provide a framework for statistical inference. We propose a mean field approximation to perform posterior inference and parameter estimation. The approximation allows a practical solution to the inference problem, {while still retaining a good degree of accuracy.} We illustrate our approach on two biologically motivated systems.

Author Information

Manfred Opper (Technische Universitaet Berlin)
Guido Sanguinetti (University of Edinburgh)

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