Examples as rendered notebooks + neural ACNet example#7
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Convert the example scripts into step-by-step Jupyter notebooks rendered in the docs site via mkdocs-jupyter (execute=false: committed, pre-run outputs). - docs/examples/*.ipynb (5): two-level copula, MLE fitting, censored survival, sampling & visualization, and a NEW neural-generator example — an ACNet (tensor-network mixture of exponentials) fit end-to-end through the Bell density (reaches mean LL 2.86 vs the true-Clayton ceiling 3.06 on synthetic d=5 data; independence = 0). Each notebook has markdown explanation cells. - mkdocs.yml: add mkdocs-jupyter; nav Examples lists the 5 notebooks. - Remove the old examples/*.py scripts, examples/README.md, the static docs/examples.md, and the now-redundant tree/pair PNGs (figures are embedded in notebook 04). - pyproject: add mkdocs-jupyter to the docs extra. README/index/quickstart point at the rendered notebooks. All notebooks pre-executed with JAX_PLATFORMS=cpu; `mkdocs build --strict` clean; llms.txt still generated.
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Per request: examples become rendered Jupyter notebooks (step-by-step), shown in the docs site, plus a new neural (ACNet) example.
docs/examples/, rendered viamkdocs-jupyter(committed pre-run outputs, no execution at build time):jax.grad. On syntheticexamples/*.py, staticexamples.md, and redundant PNGs (figures now embedded in notebook 4).mkdocs-jupyteradded to the docs extra; nav lists the notebooks.mkdocs build --strictclean; llms.txt still generated; all notebooks pre-executed (JAX_PLATFORMS=cpu).