New version: Unfold v0.7.7

[JuliaRegistrator]

• Registering package: Unfold
• Repository: https://github.com/unfoldtoolbox/Unfold.jl
• Created by: @behinger
• Version: v0.7.7
• Commit: a76a9727f4e17b2b91c20bd56cac3a8f610e2473
• Reviewed by: @behinger
• Reference: Ticket to activate JuliaRegistrator for new versions unfoldtoolbox/Unfold.jl#107 (comment)
• Description: Neuroimaging (EEG, fMRI, pupil ...) regression analysis in Julia
• Release notes:

- new structured backbone for the solver. Added ~6-7 new solvers. Split up the solver into prepare & solve functions that can be chained / modified easily. Added a reference document for exactly this.
- major bug: likelihoodratiotest was calculating wrong results (it was calculating a wrong likelihood). This lead to a breaking change in API, where now the data need to be provided as well.
- Bumped JLD to 0.5 - this means one cannot save files now and load it in older Unfold versions, but old unfold version files can still be loaded
- several small docstring fixes
- new CUDAextension, allowing to provide CuArray to automatically choose a better solver (still needs to be tested more though)
- fit now has an argument that can be set fit=false to not actually run the ´fit!` function, to do it later
- benchmarks now available comparing ~7 solver types with and without GPU, some with and without Float32. Improvements of up to 10x of the SOA-GPU solver were achieved - fit a large model with 128 channels in wopping 8 seconds! Further tests are needed though to describe the accuracy drop that is achieved by solving  `X'Xb = X'y` instead of `Xb = y` directly.

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