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The probabilistic programming library #Probula in #Scala, got a new minor release today (v.0.2.3).

The release includes a bunch of small improvements that slowly make probula usable: support for vectorized variables/plates, for-comprehensions, truncated […]

[Original post on social.dukla.ch]

$```scala val model = for a <- Gaussian("a")(0.0, 10.0) // prior b <- Gaussian("b")(0.0, 3.0) // prior σ <- UniformC("σ")(0.0, 3.0) // prior _ <- xs.plateD { x => Gaussian(a*x + b, σ) } // likelihood .observing(ys) // ... and data yield (a, b, σ) ```$

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