AugmentedGaussianProcesses.jl

Corrected Laplace ELBO
Added Poisson Likelihood for events datasets
Custom mean priors : ZeroMean, ConstantMean, EmpiricalMean (see docs)

Simplification of the likelihood and inference struct names
Documentation improvement

Complete remaking of the package

• Now only 3 models : GP, VGP and SVGP parametrized on their likelihood and inference
• Unique background for all likelihoods and inference to simplify the addition of new likelihoods
• Multioutput GPs (still some bugs there), but does not allow dependency between outputs yet
• Functions are more julian : train!(model), predict_f(model,X_test)
• Automatic plotting of the models (for 1D and 2D inputs) via Makie.plot(model)
• Sampling from the model via rand
• Multiclass likelihood is now fully functionning with multiple features described in the docs

Nothing new, just removed the integrated GradDescent

More complete documentation with full examples.
More stable predictions by replacing QuadGK.jl with Expectations.jl (but slightly slower)
Documentation improved for many functions

No major improvements

New major update,
With the new Student-T Likelihood added
Possibility to save and load trained models
Important optimization for the matrix and hyperoptimization side
GradDescent integrated to the package (temporarily)

Added a lot of documentation
Better testing
Reconstruction of the structure
First drafts of Multiclass