Hello, I am new to PPL world. I came across TF-probability and was giving it a try, but the dependency mess in TF world is a turn-off. I am planning to switch to Pyro world for my needs.
Basically, I am interested in building Hierarchical Dirichlet Process-based models for text mining/IR.
Pardon my lack of knowledge about Pyro, but can we build Bayesian Non-parametric models using Pyro (similar to https://github.com/tensorflow/probability/blob/master/tensorflow_probability/examples/jupyter_notebooks/Fitting_DPMM_Using_pSGLD.ipynb)?
Any leads on this would be highly appreciated.