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Markov Chain Monte Carlo for High-dimensional, Nonlinear Problems in Earth Science | HDSI Seminar Series

October 17 @ 1:00 pm - 2:00 pm

Earth science nearly always requires estimating models, or model parameters, from data. This could mean to infer the state of the southern ocean from ARGO floats, to compute the state of our atmosphere based on atmospheric observations of the past six hours, or to construct a resistivity model of the Earth’s subsurface from electromagnetic data. All these problems have in common that the number of unknowns is large (millions to hundreds of millions) and that the underlying processes are nonlinear. The problems also all have in common that they can be formulated as the problem of drawing samples from a high-dimensional Bayesian posterior distribution...

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