Hey guys maybe it would be a good idea to have a look at edward 23 which was built with bayesian inference in mind. It uses tensorflow as backend but I guess most of the ideas of defining RVs and distributions would be the same. Maybe the translation and switch of edward's backend form tensorflow to pytorch might not be that extremely difficult and you won’t have to start from scratch. I think it would be nice to see sth equivalent to pytorch.distributed but this time pytorch.bayesian