jpgm

A Java library for Probabilistic Graphical Models

Roadmap

1.0.0

• Implement Discrete Factor Representation
  • Base Class
    • Factor Product
  • Joint Probability Distribution
    • Independencies
• Implement Continuous Factor Representation
  • Linear Gaussian
• Bayesian Network Representation
  • Basic structure and construction
  • d-sep/independencies
• Markov Network
  • Basic structure and construction
  • d-sep
  • Partitioning/Normalization
• Inference
  • Variable Elimination
    • Elimination ordering
    • Sum-Product
    • Max-Product
• Toy Examples
  • Student example
    • Showcase current features for 1.0.0
• Documentation
  • Fully document all classes
• Testing
  • More robust testing of edge cases
    • Variables of the same name
    • Catching/Throwing errors

1.1.0

• Implement Discrete Factor Representation
  • Base Class
    • String Representations
    • inplace operations
  • Joint Probability Distribution
    • i-map of a network
    • p-map of a network
    • minimal i-map
• Implement Continuous Factor Representation
  • User defined distribution (dirichlet, etc.)
• Models
  • Factor Graph
    • Creation as a base class?
    • Conversions from other models
  • Bayesian Network Representation
    • Caching of graph queries (d-sep, trails)
    • i-equivalence
  • Markov Network
• Inference
  • Inference over generalized factor graph
• Toy Examples
  • Student example
    • Showcase current features for 1.1.0
• Documentation
  • Fully document all classes
  • Add documentation coverage
• Testing
  • More robust testing of edge cases
    • Variables of the same name
    • Catching/Throwing errors
• Logging
  • Decide upon and implement a logging structure
    • log4j/slf4j