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heat_1D

Instructions for running the 1D heat Bayesian Inverse Problem

The code for sections 2.1-2.6 of the paper can be found in the python notebook heat_1D_part1.ipynb. It generates figures 2, 3 and 4. And the code for sections 2.7 of the paper can be found in the python notebook heat_1D_part2.ipynb. It generates figure 5.

The code can take very long time to run. For experimentation, you can adjust the parameter Ns_factor in the python notebooks to a value less than one to set up the code to generate less samples. For example Ns_factor=0.01 will result in number of samples that is 1% of the original number of samples. Note, however, that generating fewer samples could potentially result in poor approximation of the posterior.