# Conceptual Gaussian Process Questions

**URL:** <https://discourse.julialang.org/t/conceptual-gaussian-process-questions/44305>\
**Category:** Probabilistic Programming\
**Created:** [August 5, 2020, 3:55am UTC](https://discourse.julialang.org/t/conceptual-gaussian-process-questions/44305 "2020-08-05T03:55:33Z")\
**Posts on this page:** 1\
**Showing post:** 13

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**Author:** ![willtebbutt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/willtebbutt/32/6790_2.png) [@willtebbutt](https://discourse.julialang.org/u/willtebbutt)\
**Post date:** [August 8, 2020, 11:49am UTC](https://discourse.julialang.org/t/conceptual-gaussian-process-questions/44305/13 "2020-08-08T11:49:06Z")

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Just so that Turing gets some air-time in this thread, here’s a Turing + Stheno example that I wrote other day here:

> [@Gaussian Process Model with Turing](https://discourse.julialang.org/t/gaussian-process-model-with-turing/42453/13):
>
> Firstly, many apologies for taking so long to reply. So it looks like the following works just fine: Turing.jl + Stheno.jl implementation using DataFrames using Distributions using Random using Stheno using Turing using Zygote # Use Zygote for AD. Be sure to use 0.4.20 rather than 0.5. Turing.setadbackend(:zygote) # Generate fake data. df = DataFrame( subject = repeat(1:5, inner=3), obese = repeat(rand(Bool, 5), inner=3), timepoint = [1,2,3,1,3,4,1,2,5,1,4,5,1,3,5], bug = ran…

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