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Abstract Details
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Activity Number:
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123
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #302463 |
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Title:
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A Bayesian Approach To Inverse Problems Via Feynman-Kac Formula
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Author(s):
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Radu Herbei*+
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Companies:
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The Ohio State University
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Address:
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1958 Neil Ave, Columbus, OH, 43210, United States of America
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Keywords:
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Bayesian inverse problem ;
Feynman-Kac ;
partial differential equations ;
diffusion process
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Abstract:
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In modern applied statistics, scientists often use physical models based on partial differential equations. Such PDEs typically do not have closed form solutions and one has to use a numerical scheme to approximate the solution over a regular grid. In the current work we make use of the Fenyman-Kac formula to provide an alternative to computationally intensive numerical schemes. We express the solution of a PDE in a probabilistic setting and then approximate it via Monte Carlo. We apply our method to a Bayesian approach to solving an oceanographic inverse problem.
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