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Computational Advancements in Data-Consistent Inversion

Project description


of Michael Pilosov

The text below is merely a placeholder taken from the MUD repo.

Analytical solutions and some associated utility functions for computing maximal updated density points for Data-Consistent Inversion.


Maximal Updated Density Points are the values which maximize an updated density, analogous to how a MAP (Maximum A-Posteriori) point maximizes a posterior density from Bayesian inversion. Updated densities differ from posteriors in that they are the solution to a different problem which seeks to match the push-forward of the updated density to a specified observed distribution.

More about the differences here...

What does this package include?


This project has been set up using PyScaffold 3.2.3. For details and usage information on PyScaffold see

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