PEtab SciML TODO

This issue acts as a TODO on things to complete for the standard:

• Add different initializationPriors. In addition the the supported priors in PEtab we should add glorot_normal, glorot_uniform as well as kaiming_normal and kaiming_uniform, where for the latter users will have to specify the gain. Need to add test cases for this.
• Add ability to set initialization for a layer via the parameters table. The following should be allowed in the parameters table: netId.layerId. Need to add test cases for this.
• Add test case where neural network parameters are constant (not estimated).
• Following #4, specify neural network output in the condition table. This will wait for PEtab v2 spec completion.
• Update the specification for PEtab SciML, and host it online in this repository. Usually I use Julia Documenter.jl for hosting docs, but I guess we should use something Python based for consistency?
• Update to use the code in src/python/petab_sciml for setting up the test cases.
• Add repository tests, specifically add tests to test the consistency between Lux.jl and PyTorch (this is already done in the net test-cases, but this should be refactored to a proper test directory).
• Add and test for the yaml model specification and parameter import with PyTorch?
• Add utility functions for creating array HDF5 files
• Release version 0.1.0

Feel free to add any more points you might find relevant. Once the above points are addressed, I think the extension should be close to complete.

The checklist covers PEtab SciML specification, Python, Julia/Lux.jl, PyTorch, YAML, and repository tests, but only the 0.1.0 release remains unchecked. Start by reviewing the repository's release metadata and workflow; done means version 0.1.0 is released and the final checklist item is checked.