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Generalize ensemble Kalman algorithms to work with complex learnable parameters

Open ilopezgp opened this issue 2 years ago • 0 comments

For users that want to learn complex parameters (e.g., coefficients within an FNO), it would be useful to generalize the algorithms to directly allow them to work with complex numbers.

This would require modifying the covariances to use complex conjugates, and generalizing input types since

julia> b = sqrt(Complex(-2))
0.0 + 1.4142135623730951im

julia> isa(b, AbstractFloat)
false

ilopezgp avatar Nov 02 '22 16:11 ilopezgp