Add UEA (Universal Equivariant Approximator) architecture

[frostedoyster]

This PR adds the UEA architecture

Contributor (creator of pull-request) checklist

• Add your architecture to the experimental/stable folder. See the
  [docs/src/dev-docs/architecture-life-cycle.rst](Architecture life cycle) document for
  requirements.
  src/metatrain/experimental/<architecture_name>
• Add default hyperparameter file to
  src/metatrain/experimental/<architecture_name>/default-hypers.yml
• Add a .yml file into github workflows .github/workflow/<architecture_name>.yml
• Architecture dependencies entry in the optional-dependencies section in the
  pyproject.toml
• Tests: torch-scriptability, basic functionality (invariance, fitting, prediction)
• Add maintainers as codeowners in CODEOWNERS

Reviewer checklist

New experimental architectures

• Capability to fit at least a single quantity and predict it, verified through CI
  tests.
• Compatibility with JIT compilation using TorchScript <https://pytorch.org/docs/stable/jit.html>_.
• Provision of reasonable default hyperparameters.
• A contact person designated as the maintainer, mentioned in __maintainers__ and the CODEOWNERS file
• All external dependencies must be pip-installable. While not required to be on
  PyPI, a public git repository or another public URL with a repository is acceptable.

New stable architectures

• Provision of regression prediction tests with a small (not exported) checkpoint
  file.
• Comprehensive architecture documentation
• If an architecture has external dependencies, all must be publicly available on
  PyPI.
• Adherence to the standard output infrastructure of metatrain, including
  logging and model save locations.

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📚 Documentation preview 📚: https://metatrain--660.org.readthedocs.build/en/660/