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Co-authored-by: Hong Ge <[email protected]>
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Red-Portal and yebai authored May 27, 2024
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[AdvancedVI](https://github.com/TuringLang/AdvancedVI.jl) provides implementations of variational inference (VI) algorithms.
VI algorithms perform scalable and computationally efficient Bayesian inference at the cost of asymptotic exactness.
`AdvancedVI` is part of the [Turing](https://turinglang.org/stable/) probabilistic programming ecosystem.
The purpose of this package is to provide a common accessible interface for various VI algorithms and utilities so that other packages, e.g. `Turing`, only need to write a light wrapper for integration.
This package provides a common accessible interface for various VI algorithms and utilities so that other packages, e.g. `Turing`, only need to write a light wrapper for integration.
For example, `Turing` combines `Turing.Model`s with `AdvancedVI.ADVI` and [`Bijectors`](https://github.com/TuringLang/Bijectors.jl) by simply converting a `Turing.Model` into a [`LogDensityProblem`](https://github.com/tpapp/LogDensityProblems.jl) and extracting a corresponding `Bijectors.bijector`.

## Examples
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