As it stands, a significant portion of the SVI tutorial code is written in markdown code blocks, rather than standalone Jupyter cells. When formatted this way, the tutorial's notebook cannot be excecuted and experimented with by the reader. I suggest that the markdown code blocks should be refactored into Jupyter code ce

tfd.Categorical.quantile not working

Ankit Shah and I are trying to use Gen to support a project and would love the addition of a dirichlet distribution

Following my post here, https://forum.pyro.ai/t/dirichlet-process-gaussian-mixture-model-typeerror-for-small-concentration-parameter/2685, when one tries creating a Dirichlet Process Mixture Model with 0 mixture components, the error message returned is

TypeError: iota shape must have every element be nonnegative, got (-1,).

This isn't helpful in identifying the source of the error. Could

The current example on MDN from Edward tutorials needs small modifications to run on edward2. Documentation covering these modifications will be appreciated.

It is hard to keep track of how subsequent changes affect the sampling performance of the library. We should add ˋpytest-benchmark` to the test suite and use related github action to run benchmarks automatically.

There are a variety of interesting optimisations that can be performed on kernels of the form

k(x, z) = w_1 * k_1(x, z) + w_2 * k_2(x, z) + ... + w_L k_L(x, z)

A naive recursive implementation in terms of the current Sum and Scaled kernels hides opportunities for parallelism in the computation of each term, and the summation over terms.

Notable examples of kernels with th

https://github.com/probcomp/metaprob/blob/c1a01ea02c51ea0f8fedebd45954914d7645bde9/src/metaprob/distributions.clj#L55-L60

In the scorer, argument x should be checked to lie in the interval [a,b].