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Published September 11, 2023 | Version v3.9.3
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ReactiveMP.jl: a Julia package for automatic Bayesian inference on a factor graph with reactive message passing.

  • 1. Eindhoven University of Technology Eindhoven

Description

ReactiveMP v3.9.3

Diff since v3.9.2

Closed issues:

  • The documentation needs "how to add nodes and rules" (#296)
  • @call_rule does not play nicely with addons (#332)
  • CVI Support for the Categorical Distribution (#334)
  • Rand for GammaShapeRate is broken. (#337)
  • 'v_a_vT' is slow and named wrong (#343)
  • Create sparse matrix structure for outer product of StandardBasisVector (#344)
  • MethodError: *(::LinearAlgebra.Diagonal{Float64, Vector{Float64}}, ::StandardBasisVector{Float64}) is ambiguous. (#348)

Merged pull requests:

  • CompatHelper: bump compat for LazyArrays to 1, (keep existing compat) (#304) (@github-actions[bot])
  • CompatHelper: bump compat for StatsBase to 0.34, (keep existing compat) (#313) (@github-actions[bot])
  • Improving the prod function for Gaussian Distributions in CVI Approximation (#335) (@Nimrais)
  • CVI Support for the Categorical Distribution (#336) (@Nimrais)
  • Add Half-normal node (#338) (@albertpod)
  • fix sampling from GammaShapeRate (#339) (@bvdmitri)
  • Fix printing bug (#345) (@bartvanerp)
  • Allow returning addons from the @call_rule (#346) (@bvdmitri)
  • Fix v_a_vT and StandardBasisVector (#347) (@bvdmitri)
  • Fix ambiguity error for * between Diagonal and StandardBasisVector (#349) (@bvdmitri)

Notes

Please cite this research as below.

Files

biaslab/ReactiveMP.jl-v3.9.3.zip

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