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In Bambi which uses PyMC3, it's possible to plot a smoothed histogram (using kernel density estimation) of the marginal posteriors of each stochastic random variable. For example see https://docs.pymc…
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This is related to #82 but should be it’s own issue.
Currently we rely on users to use the model weights to create the appropriate mixture of predictive distributions. We should recommend (and dem…
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Hi,
Is it true that each element of ```mu``` and ```sigma2``` in [leave_one_out_pseudo_likelihood.py](https://github.com/cornellius-gp/gpytorch/blob/master/gpytorch/mlls/leave_one_out_pseudo_likeli…
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Hi, I wrote a small function that does a job similar to `prior_from_idata`, but can also handle log-normal distributions. @ricardoV94 suggested it could find its place in `pymc-experimental`, or at le…
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[Rezende and Mohamed 2015](https://arxiv.org/abs/1505.05770) is a classic paper on using normalizing flows, rather than e.g. mean-field approximations, for variational inference. Normalizing flows are…
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I wonder the difference between Bayesian MCMC model and Bayesian regression analysis model.
The tensorflow_probability library is being used. The code has been imported from Excel into the target val…
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See the attached Vagrantfile for the build environment:
[Vagrantfile.txt](https://github.com/posterior/loom/files/1206108/Vagrantfile.txt)
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It would be useful to complete the prior rating curve tabs in the same way as the posterior rating curve tabs (table, etc.).
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Hi,
I am trying to use tensorflow probability to learn a Bayesian neural networks. I want to learn the responses y_t based on input features x_t, i.e.
` y_t = f(x_t) + eps`
where f(x_t) is th…
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### Describe the issue:
When applying the ordered transform to the ZSN the model suffers a `-inf` logp.
### Reproduceable code example:
```python
with pm.Model() as pmodel:
pm.ZeroSumNo…