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Infer.NET User Guide
Introduction
What is Infer.NET?
A simple example
How Infer.NET works
Frequently Asked Questions
Building probabilistic models
The Infer.NET modelling API
Creating variables
Applying functions and operators to variables
Attaching constraints to variables
Working with arrays and ranges
Arrays and ranges
ForEach blocks
Jagged arrays
Indexing arrays by observed variables
Branching on variables to create mixture models
Computing model evidence for model selection
Factors and constraints
Distribution factors
Boolean and comparison operations
Arithmetic and mathematical operations
Linear algebra factors
Constraints
Miscellaneous factors
List of factors and constraints
Advanced model building
Adding attributes to your model
The Model Specification Language
Running inference on your model
Running inference
Inference engine settings
Working with different inference algorithms
Controlling how inference is performed
Customising the algorithm initialisation
Using a precompiled inference algorithm
Structure of generated inference code
Debugging inference
Improving the speed and accuracy of inference
Sharing variables between models
Extending Infer.NET
How to add a new distribution type
How to add new factors and message operators
How to add a new constraint
Calling Infer.NET from other languages
F#
Variable Arrays in F#
Inference in F#
Operator Overloading in F#
Imperative Statement Blocks in F#
C++/CLI
Iron Python
Mono
Tutorials and examples
The Examples Browser
Tutorials:
Two coins
Truncated Gaussian
Learning a Gaussian
Bayes point machine
Clinical trial
Mixture of Gaussians
Examples:
Click model
Click through model
Image classifier example
Multi-class classification
:
Bayes point machine
,
with shared variables
,
sparse version
Clinical trial
Monty Hall problem
How-to guides:
How to handle missing data
How to represent large irregular graphs
Code documentation
Release change history
Last modified at 8/3/2009 9:09 AM by
John Guiver
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