Gaussian Process package based on data augmentation, sparsity and natural gradients
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Published by theogf over 5 years ago
Corrected Laplace ELBO
Added Poisson Likelihood for events datasets
Custom mean priors : ZeroMean, ConstantMean, EmpiricalMean (see docs)
Published by theogf over 5 years ago
Simplification of the likelihood and inference struct names
Documentation improvement
Published by theogf over 5 years ago
GP
, VGP
and SVGP
parametrized on their likelihood and inferencetrain!(model)
, predict_f(model,X_test)
Makie.plot(model)
rand
Published by theogf almost 6 years ago
Nothing new, just removed the integrated GradDescent
Published by theogf almost 6 years ago
Published by theogf almost 6 years ago
More complete documentation with full examples.
More stable predictions by replacing QuadGK.jl with Expectations.jl (but slightly slower)
Documentation improved for many functions
Published by theogf about 6 years ago
No major improvements
Published by theogf about 6 years ago
Published by theogf about 6 years ago
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)
Published by theogf about 6 years ago
Added a lot of documentation
Better testing
Reconstruction of the structure
First drafts of Multiclass