Make basic INLA interface and simple marginalisation routine #533
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ricardoV94
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Aug 12, 2025
Michal-Novomestsky
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ColtAllen
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Aug 27, 2025
| *args, | ||
| Q: TensorVariable, | ||
| minimizer_seed: int, | ||
| minimizer_kwargs: dict = {"method": "L-BFGS-B", "optimizer_kwargs": {"tol": 1e-8}}, |
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This may create unpredictable behavior if any changes are made to the minimizer kwargs. Let's make None the default argument and add a conditional for the default kwargs.
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I believe I coded it up like that originally but Theo had the exact opposite opinion haha, thoughts @theorashid ?
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| # logp(y | x, params) | ||
| log_likelihood = pt.sum( | ||
| [logp_term.sum() for value, logp_term in logps_dict.items() if value is not marginalized_vv] |
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pt.switch could work for this I think.
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Addresses #532 and #344.
Relies on pymc-devs/pytensor#1582.