Aggregate elements based on multi-valued references.
Abstract base class for elements representing function application.
Application of a function to one argument.
Application of a function to two arguments.
Application of a function to three arguments.
Application of a function to four arguments.
Application of a function to five arguments.
The Atomic trait characterizes elements that do not depend on any related elements.
A distribution in which the probabilities are constants and the outcomes are Elements.
A coin toss in which the weight is a fixed constant.
A distribution in which both the probabilities and the outcomes are values.
Elements whose values can be cached and reused.
A CachingChain is an implementation of Chain with a 1000 element cache
A Chain(parent, fcn) represents the process that first generates a value for the parent, then applies fcn to get a new Element, and finally generates a value from that new Element.
A distribution in which both the probabilities and outcomes are Elements.
A coin toss where the weight is itself an element.
A distribution in which the probabilities are Elements and the outcomes are values.
Evidence representing a condition on an element.
Elements that always produce the same value.
Evidence representing a constraint on an element.
Figaro's reflection allows you to create a Figaro element by providing the name of the element class as a string and its arguments as elements.
Elements with no randomness.
Distributions with randomly chosen outcomes that are themselves specified by Elements.
An Element is the core component of a probabilistic model.
An element collection contains elements.
Evidence that can be associated with an element.
Weighted coin tosses, where the weight itself might be random.
Elements whose values can be cached and reused as long as the arguments are cacheable.
An indirect reference to an element, first using the head to refer to an element collection, and then referring to the tail from within the element collection.
Element that converts a sequence of elements into an element over sequences.
Evidence representing a log constraint on an element.
A direct reference to an element by its name.
Association of evidence with a reference.
A NonCachingChain is an implementation of Chain with a single element cache
Evidence representing observing a particular value for the element.
Trait of learnable parameters.
Trait of elements which accept learnable parameters.
A coin toss where the weight is specified by a learnable parameter.
A distribution in which the probabilities are learnable parameters and the outcomes are values.
Pragmas are hints to algorithms that are associated with elements.
A reference to an element.
Element representing the value of a reference.
Distributions with randomly chosen outcomes.
Element representing a single-valued reference.
A universe is a collection of elements that can be used by a reasoning algorithm.