[HN Gopher] Reactive Probabilistic Programming
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       Reactive Probabilistic Programming
        
       Author : matt_d
       Score  : 40 points
       Date   : 2020-07-20 20:09 UTC (2 hours ago)
        
 (HTM) web link (arxiv.org)
 (TXT) w3m dump (arxiv.org)
        
       | jefft255 wrote:
       | From my robotics point of view, probabilistic programming looks
       | really attractive, and this paper seems to give very
       | interesting/neat examples for control and Kalman filtering.
       | 
       | I wonder what has prevented these languages from being widely
       | adopted by the robotics community? My suspicion is that it's
       | always easier to work with general purpose languages, but even
       | then "probabilistic programming libraries" for Python, e.g. Pyro
       | or Edward, haven't really taken off either... Most people write
       | SLAM algorithms in C++ and don't pay much attention to what the
       | PPL people are doing.
        
         | ssivark wrote:
         | I think we're still on the path to making (efficient) inference
         | work for broader classes of problems (expressive problem
         | formulation). One of the most interesting recent projects I've
         | come across is "Gen" by the probcomp group at MIT (BTW, a lot
         | of interesting work related to PPL seems to be happening in the
         | Julia language).
        
           | mccoyb wrote:
           | I'm happy someone mentioned the community in Julia!
           | 
           | We're always looking for interested people to join and try
           | out some of the systems. For easy access to some of the
           | active PP frameworks:
           | 
           | Turing.jl https://turing.ml/dev/
           | 
           | Gen.jl https://www.gen.dev/
           | 
           | Soss.jl https://github.com/cscherrer/Soss.jl
           | 
           | Jaynes.jl https://github.com/femtomc/Jaynes.jl
           | 
           | Why so many? The design space is just beginning to be well-
           | explored. Gen.jl + Jaynes.jl are really research projects
           | aiming to push the boundary of what you can express inside a
           | PP framework. Gen.jl is much more mature than the latter
           | (which I develop) and has tons of great and thought-provoking
           | documentation. Turing.jl is also very mature, and they have a
           | great number of resources showing how to express a number of
           | classic models in their language, as well as how to compose
           | sampling-based inference algorithms. Soss.jl is also very
           | cool - and works by AST re-writing. I'm not sure the state of
           | the docs for Soss.jl - but the researchers for each of these
           | systems are always willing to discuss the systems on the
           | Julia Slack or Zulia!
        
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       (page generated 2020-07-20 23:00 UTC)