pymc
https://github.com/pymc-devs/pymc
Python
Bayesian Modeling in Python
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- Issues
- Derive Categorical from Argmin/Argmax
- Add a function to create a tensor that represents the loop over the posterior
- Graceful incompatible coords handling
- Implemented icdf for Categorical distribution and add shape/broadcasting tests.
- Don't use deprecated batched_dot
- premshaw04/#7581/Fix Censored doc type hints and add example for partially censored array inputs
- Remove `model.check_bounds` in favor of graph introspection
- Use pack and unpack in `join_nonshared_inputs`
- Compute Metropolis average accept probability with `logsumexp`
- BUG: `find_constants` helper function is inconsistent
- Docs
- Python not yet supported