Timeline for What makes parallel/distributed probabilistic inference difficult to implement?
Current License: CC BY-SA 3.0
7 events
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| May 23, 2017 at 12:39 | history | edited | CommunityBot |
replaced http://stackoverflow.com/ with https://stackoverflow.com/
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| Mar 30, 2016 at 2:30 | comment | added | Ben Goodrich | I didn't think it answered the heart of the OP's question, but I would change it to an answer if @Bar wanted me to. | |
| Mar 29, 2016 at 19:59 | comment | added | Sycorax♦ | @BenGoodrich Welcome to CV! You're probably the most qualified CV user, if not the single most-qualified person, to comment on how Stan works, so perhaps this comment could be submitted as an answer? | |
| Mar 29, 2016 at 16:19 | vote | accept | Bar | ||
| Mar 29, 2016 at 14:46 | answer | added | jaradniemi | timeline score: 4 | |
| Mar 29, 2016 at 13:32 | comment | added | Ben Goodrich | In the case of Stan, there are technical obstacles to performing auto-differentiation in parallel within a chain. As far as I understand it, the expression tree that Stan walks through to evaluate the gradient of the log-posterior with respect to the parameters (currently) has to be handled serially to ensure that it works correctly. There is some movement, or at least interest, in parallelizing some parts of Stan that internally handle the derivatives analytically rather than relying on the auto-differentiations mechanism. The other probabilistic programming languages do not face this issue. | |
| Mar 29, 2016 at 13:13 | history | asked | Bar | CC BY-SA 3.0 |