docs: add how-to guide for embedding time-series data using CausalCNN and Transformer

[satwiksps]

Summary

This PR adds a new how-to guide demonstrating how to use CausalCNNEmbedding and TransformerEmbedding to handle sequential (time-series) data in sbi.

Details

• Uses synthetic time-series data (torch.randn)
• Shows integration with posterior_nn and NPE
• Based on discussions in docs: add tutorial / how-to-guide for embedding time-series data, e.g., using causalCNNs #1523
• Keeps examples minimal, avoiding SIR boilerplate
• Adds entry under "Neural nets" in how-to guides

Checklist

• Notebook runs without errors
• Added entry in docs/how_to_guide/index.rst
• Verified build via make html
• Consistent style with other how-to guides

[janfb]

looks very good already!

I only have two minor comments and added one request for creating a related issue.

[janfb]

Great addition to the docs, thanks a lot @satwiksps - well done! 👏

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 84.62%. Comparing base (6ffe7b6) to head (9082781).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

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- Coverage   88.48%   84.62%   -3.86%     
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  Files         137      137              
  Lines       11470    11470              
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- Hits        10149     9707     -442     
- Misses       1321     1763     +442     

Flag	Coverage Δ
unittests	84.62% <ø> (-3.86%)	⬇️

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see 29 files with indirect coverage changes

[satwiksps]

The CI run failed due to minor pre-commit / Ruff formatting issues (import order, unused import, and whitespace).
I’m addressing these locally and will push the corrected notebook shortly. Thanks for your patience!