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Efficient and Flexible Inference for Stochastic Systems
Stefan Bauer · Nico S Gorbach · Djordje Miladinovic · Joachim M Buhmann

Tue Dec 05 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #8 #None

Many real world dynamical systems are described by stochastic differential equations. Thus parameter inference is a challenging and important problem in many disciplines. We provide a grid free and flexible algorithm offering parameter and state inference for stochastic systems and compare our approch based on variational approximations to state of the art methods showing significant advantages both in runtime and accuracy.

Author Information

Stefan Bauer (ETH Zürich)
Nico S Gorbach (Swiss Federal Institute of Technology Zurich (ETHZ))
Djordje Miladinovic (ETH Zurich)
Joachim M Buhmann (ETH Zurich)

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