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Since everything in TemporalGPs.jl is build around SSMs, it should be easy to obtain filtered posteriors of various forms, e.g. p(f_t|Y_0,...,Y_t) or p(f_t|Y_0,...,Y_{t-1}) for all t in some range. It seems that e.g. the latter can be done by using some internals like so:
functionone_step_ahead_predictions(f, x, y)
fx =f(x, obs_noise +1e-6)
lgssm =build_lgssm(fx)
F =vcat(x0(lgssm), _filter(lgssm, y)[1:end-1])
E =emissions(lgssm)
returnpredict.(F, E)
end
but
not having a complete understanding of the internals, I'm not sure this is correct
It would be nice to expose this (or the correct version) as a public API
The text was updated successfully, but these errors were encountered:
Since everything in TemporalGPs.jl is build around SSMs, it should be easy to obtain filtered posteriors of various forms, e.g.
p(f_t|Y_0,...,Y_t)
orp(f_t|Y_0,...,Y_{t-1})
for allt
in some range. It seems that e.g. the latter can be done by using some internals like so:but
The text was updated successfully, but these errors were encountered: