Methods › General › Variational Optimization › ASVI
Automatic Structured Variational Inference
ASVI
Introduced by Luca Ambrogioni et al. in Automatic structured variational inference
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Automatic Structured Variational Inference (ASVI) is a fully automated method for constructing structured variational families, inspired by the closed-form update in conjugate Bayesian models. These convex-update families incorporate the forward pass of the input probabilistic program and can therefore capture complex statistical dependencies. Convex-update families have the same space and time complexity as the input probabilistic program and are therefore tractable for a very large family of models including both continuous and discrete variables.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Automatic variational inference with cascading flows 9 Feb 2021 · 0 repositories · arXiv:2102.04801
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Automatic structured variational inference 3 Feb 2020 · 2 repositories · arXiv:2002.00643
Tasks archive 2025-07-28
2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Variational Inference | 2 |
| Probabilistic Programming | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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