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I don't see any reference to infer.net [1]. Aren't both of them related? [1] http://research.microsoft.com/en-us/um/cambridge/projects/infernet/ http://researc
by paperwork 12y ago
I don't see any reference to infer.net [1]. Aren't both of them related?
[1] http://research.microsoft.com/en-us/um/cambridge/projects/infernet/ http://research.microsoft.com/en-us/um/cambridge/projects/in...
edit: typo
- ot 12y agoThey are related in that they are both probabilistic programming languages, but the similarities stop there. First, infer.net is a DSEL of C# implemented as a library, while this is a new language. More substantially, infer.net is designed to use variational inference, which limits the class of graphical models that can be supported, while R2 seems to be based on sampling hence has no limits on the models it can represent. A more similar approach would be Church (http://projects.csail.mit.edu/church/wiki/Church http://projects.csail.mit.edu/church/wiki/Church), a probabilistic language based on Scheme. Of course, the downside of sampling is that inference is orders of magnitude slower, and there's no principled way to know when it converges, that's why many people prefer variational inference.
- eli_gottlieb 12y agoOf course, both variational inference and sampling-based inference are exponentially faster than actual exact probability calculations.