I see that PyMC3 has a high level Gaussian Process (GP) API. GPs are quite abstract and so I’d like to get more familiarity with them before letting the API do all the thinking for me. I stumbled on this blog which implements GPs in python from scratch, which has been very helpful. The author optim…

I didn’t have the chance to read the blog you linked to. [image] jbuddy_13: How is the Bayesian/PyMC3 approach different than the frequentist one? (It seems that rather than optimizing kernel hyperparameters, they’re sampled via HMC.) The difference you are hinting at here is the difference…

Vanilla implementation of Gaussian Process in PyMC3?

Questions

jbuddy_13 January 4, 2021, 2:59pm 7

Thanks, very helpful!

Topic		Replies	Views
Gaussian Process Regression level 1 inference: Re-producing Mauna Loa CO2 Example with PyMC3 Questions	10	2244	August 16, 2017
Multiple (uncertain) function observations of the same Gaussian process Questions	15	6568	October 16, 2017
Multidimensional gaussian process Questions	55	10240	October 22, 2020
Bayesian model calibration with Gaussian Process Questions	18	4962	December 9, 2021
GP model and prior prediction analysis gaussian_process , modeling	1	434	June 15, 2022

Vanilla implementation of Gaussian Process in PyMC3?

Related topics