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License: MIT License
The Automatic Statistician basic gpflow implementation
License: MIT License
Kernels need associated priors from which parameters are sampled for optimisation restarts. Kernel classes should come with defaults, and these should also be modifiable at run-time.
Parameters for `fixed' (previously optimised) bits of the kernel should not be touched when new parameters are sampled i.e. they are initialised at their previous optimal values.
I believe the periodic kernel in GPflow is not the same periodic kernel as used in the Autostat papers -- it doesn't have quite the same interpretation.
This needs looking into, we might need to code an implementation of the correct kernel, eq 4.31 in the GP book.
GP book:
http://www.gaussianprocess.org/gpml/chapters/RW4.pdf
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