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Description
A features table will also be compiled for the various PPLs. These may include:
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support / workarounds for missing data, with MWE.
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support / workarounds for ragged arrays, with MWE.
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support / workarounds for inference of discrete parameters, with MWE
- Nimble and Pyro supports direct inference on discrete parameters. The recommended workaround in other PPL's is marginalizing discrete parameters, but this is not always possible.
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support for automatic differentiation
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Customizability
- e.g. For MCMC, using a custom (user-provided) implementation to update a subset of model parameters, and use default update mechanisms (Metropolis-within-Gibbs or HMC) for the other parameters.
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support for HMC, Metropolis-within-Gibbs, ADVI / BBVI, and auto-tuning for each PPL.
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The table below is an example of what the Feature Comparisons table could look like.
Turing | STAN | Pyro | Nimble | TFP | |
---|---|---|---|---|---|
Supports inference for discrete parameters |
|
No (workaround) | Yes | Yes | No (workaround) |
Supports missing data |
|
|
|
Yes | No (workaround) |
Supports AD |
|
|
|
|
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Supports customization of MCMC |
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|
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|
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Supports HMC |
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|
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Supports NUTS |
|
|
|
|
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Supports ADVI |
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|
|
|
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etc. |
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