Pathwise sampling

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  • #65 by @rossviljoen — closed without merging

Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
20/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
julia
Domain
machine-learning

Research direction

The issue names no repository files or tests; start by reading the cited Wilson et al. paper and reviewing SparseGaussianProcesses.jl. Compare that implementation with the repository's AbstractGPs integration, then define the scope and completion criteria for pathwise posterior sampling.

Written by the indexing model from the issue text.

Description

It would be nice to eventually add pathwise posterior sampling from [1].

Essentially, reimplement https://github.com/aterenin/SparseGaussianProcesses.jl but using AbstractGPs etc.

[1] Wilson, James, et al. "Efficiently sampling functions from Gaussian process posteriors." International Conference on Machine Learning. PMLR, 2020. https://arxiv.org/abs/2002.09309

Dominant language
Julia
Stars
37
Forks
9
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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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