🚀 PlantingSpace seeks a Bayesian Software Engineer to fuse Bayesian stats with symbolic AI for verifiable multi‑step reasoning. Remote (CET). Stack: Julia + Rust/OCaml/Clojure/C++/Haskell, MCMC/SMC/VI. #Bayesian #ProbabilisticProgramming #AI #Remote #Julia aihackerjobs.com/company/plan...

Discrete probabilistic programs can be compiled into weighted automata for posterior computation, avoiding sampling or variational approximations. Read more: https://getnews.me/weighted-automata-enable-exact-inference-for-discrete-probabilistic-programs/ #weightedautomata #probabilisticprogramming

Sometimes #Bayesian Modeler's obsession with #Stan feels almost cult-like. There are way more flexible #ProbabilisticProgramming packages like #NIMLE in #R, #PyMC in #Python, and #Turing in #Julia. Personally, I think all these other packages are way more beginner friendly than Stan.

#ProbabilisticProgramming sits in between the fields of #MachineLearning and #ProgrammingLanguages, and this means it's often challenging to communicate PPL research broadly to either of the ML and PL communities.

"Program Analysis of Probabilistic Programs"
https://arxiv.org/abs/2204.06868

My PhD thesis is now available on arXiv!

Contains:
- A short intro to #BayesianInference
- An intro to #ProbabilisticProgramming with examples in different PPLs
- PPL program analysis papers with...

After being asked many times if the code is available, I'm pleased to announce that SlicStan is finally open source! 🎉 If you are interested in seeing some #ProbabilisticProgramming transformations for @mcmc_stan then head to https://github.com/mgorinova/SlicStan

Written in 100%...

#POPL2019 has been excellent so far. Can't wait for an entire day of languages for inference (#LAFI) tomorrow and two (!!!) #ProbabilisticProgramming sessions + a #MachineLearning session on Wednesday!