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noise is a term used for the error term in statistical models and in signal processing. It could be white noise, colored noise or otherwise.

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best loss function to fit model if observations contain montecarlo noise?

seems there is quite some loss of information in this step (if I make the grid too coarse then a lot of detail is lost, if I make the grid too dense, then the resulting resampled values still contain noise … about using L1 regression instead of L2, but this probably could only work if the resulting spherical harmonics could perfectly represent the ground truth... generally I have a lot more (monte carlo noise
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