## New features

- [pyro.factor](http://docs.pyro.ai/en/stable/primitives.html#pyro.factor) to add arbitrary log probability factor to a probabilistic model.
- Conditional MADE Autoregressive Network available in [pyro.nn](http://docs.pyro.ai/en/stable/nn.html#pyro.nn.auto_reg_nn.ConditionalAutoRegressiveNN).
- Tutorial on [adaptive experiment design](http://pyro.ai/examples/working_memory.html) for studying working memory.
- KL divergence for `Delta` and `Independent` distributions.
- A fast `n log(n)` implementation of the [Continuous Ranked Probability Score (CRPS)](https://www.stat.washington.edu/raftery/Research/PDF/Gneiting2007jasa.pdf) for sample sets: [pyro.ops.stats.crps_empirical](http://docs.pyro.ai/en/dev/ops.html#pyro.ops.stats.crps_empirical)

## Code changes and bug fixes

- Moved `pyro.generic` to a separate [pyro-api](https://github.com/pyro-ppl/pyro-api) package.
- Minor changes to ensure compatibility with [pyro-api](https://github.com/pyro-ppl/pyro-api), a generic modeling and inference API for dispatch to different Pyro backends.
- Improve numerical stability of MixtureOfDiagonals distribution using `logsumexp` operation.
- Improved U-Turn check condition in NUTS for better sampling efficiency.
- Reorganized `constraints` and `transforms` module to match `torch.distributions`.
- Fixed AutoGuide intitialization stragtegies, resolving a bug in `init_to_median`.