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Review on the JCON Paper #27
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In a second part I will add a few comments on the documentation and the code in a few days. |
Here is part II on the documentation; I did not yet look deeply into the actual implementations, but the code snippets I saw look nice. Concerning the code:
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These are a few comments on the JCON paper review at JuliaCon/proceedings-review#179.
I marked a few things in the PDF, and wrote additional notes. They are numbered to discuss them.
Maybe the best way to address these is in a PR.
Review ExponentialFamilyManifolds JCON
.jl
for clarity? (I only marked the first 3 and a few throughout)ManifoldsBase.jl
? That fits a bit better than the mention ofManifolds.jl
in the sentence afterwardsNaturalParametersManifold <: AbstractManifold
be correct here? Maybe even `ManifoldsBase.AbstractManifold (though that is a bit long-ish)ProductManifold
is already available fromManifoldsBase.jl
,Manifolds.jl
(also a bit of a heavy dependency) would not be necessary for thisget_natural_manifold
work? What are its two arguments? Maybe a link to the docs would be nice hereretract(M, p, X, m)
starting fromp
in directionX
is missing the retraction methodm
here, otherwise it is equivalent to just callingexp(M, p, X)
unless thedefault_retraction_method(M)
is overwritten accordingly, but then that method should be mentioned againManifolds.jl
since the positive numbers are from there. The footnote is a bit misleading, it might be read in a way, thatPositiveNumbers
is actually implemented inexponentialFamilyManifolds.jl
as wellchange_representer
. On positive numbers you might just be slightly wrong, but it would be better to actually change the representer here as wellIn principle you (implicitly) do the same in Code 4, just that there Fisher is the metric you aim for.
We just do not have Fisher-Rao much in
Manifolds.jl
but that hcnage is the same as you would need in Code 1 as well, unlessM
is Euclidean.📋
10.21105.jcon.00172.pdf
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