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Releases: biaslab/ForneyLab.jl

v0.12.0

11 May 15:07
005a16c
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ForneyLab v0.12.0

Diff since v0.11.4

Closed issues:

  • Use PDMats.jl to work with positive-definite matrices (#30)
  • Cryptic error messages (#27)
  • Write a "how to build a node" demo (#29)
  • Improve error message for algo contruction on model with dangling edges (#70)
  • How to implement boolean operations/factors for binary random variables, or more generally conditional probability tables? (#100)
  • Probability density estimation for marginals parameterised with SampleList (#137)
  • ERROR: LoadError: KeyError: key nothing not found (#146)
  • Error: No applicable marginal update rule for GaussianMeanVariance node with inbound types: Message{GaussianWeightedMeanPrecision}, Message{GaussianMeanVariance} (#194)
  • Multiplication of two categorical variables (#197)
  • Incorrect outbound message update rules for GaussianMeanVariance (#198)
  • Where are parameters stored in ForneyLab.Bernoulli? (#199)
  • ForneyLab.step! must be explicitly imported (#200)

Merged pull requests:

v0.11.4

12 Jan 10:03
be20b84
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ForneyLab v0.11.4

Diff since v0.11.3

Closed issues:

  • Algorithm construction bug (Nonlinear node) (#166)
  • Question: Can ForneyLab do parameter learning and graph structure learning? (#176)
  • code generation for repetitive graph structure (#179)
  • Belief Propagation (#185)

Merged pull requests:

v0.11.3

22 Jul 15:06
5d9110e
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ForneyLab v0.11.3

Diff since v0.11.2

Closed issues:

  • Improve stability when inverting positive definite matrices (#86)
  • Turing, SampledSignals and ForneyLab compatibility issues (#129)
  • After last updates, ForneyLab cannot build message passing algorithm. (#132)
  • Scheduler fails for posterior factors surrounding Addition node (#142)
  • Confidence Intervals on parameters (#148)
  • Free energy code generation using custom parameterized factor nodes (#149)
  • Naive beginner's question - categorical variable input (#152)
  • Stability of the log(det()) function (#153)
  • Resulting Gaussians improper (#156)
  • messagePassingAlgorithm not found (#159)
  • MethodError: no method matching length(::Variable) (#161)
  • KeyError: key :log_pdf not found (#162)

Merged pull requests:

ForneyLab.jl v0.11.2

22 Oct 16:51
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  • Extended message passing rules around Equality node
  • New demo with estimation of player skill ratings
  • Bug fixes and improvements

ForneyLab.jl v0.11.1

15 Sep 10:57
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  • Unified message passing algorithm construction
  • New approximation method for Nonlinear nodes
  • New sampling-based rules for Gamma, Beta, and Dirichlet distributions
  • Automated documentation builds

ForneyLab.jl v0.11.0

12 Aug 13:29
3b74051
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  • Implement support for sequential Monte-Carlo
  • Implement support for local variational methods
  • Decouple algorithm assembly from code generation
  • Extend Nonlinear node implementation to multiple arguments
  • Refactor recognition factorization handling

ForneyLab.jl v0.10.0

02 Sep 08:35
4abfdc0
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  • New implementation of Nonlinear node using unscented transform
  • Changes in update rule naming scheme (Void -> V is substituted by Nothing -> N)
  • Code style guide

ForneyLab.jl v0.9.2

08 May 18:03
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  • Poisson node implementation
  • New documentation system
  • Minor fixes (#14, #15, #32, #33)

ForneyLab.jl version 0.9.1

24 Nov 13:38
e21ade3
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This version incorporates some minor changes that enable more accurate backward propagation through nonlinear nodes.

ForneyLab.jl v0.9.0

06 Sep 10:14
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This release migrates ForneyLab.jl to Julia v0.7 and v1.0.