Packages

  • package root
    Definition Classes
    root
  • package provingground

    This is work towards automated theorem proving based on learning, using homotopy type theory (HoTT) as foundations and natural language processing.

    This is work towards automated theorem proving based on learning, using homotopy type theory (HoTT) as foundations and natural language processing.

    The implementation of homotopy type theory is split into:

    • the object HoTT with terms, types, functions and dependent functions, pairs etc
    • the package induction with general inductive types and recursion/induction on these.

    The learning package has the code for learning.

    Scala code, including the spire library, is integrated with homotopy type theory in the scalahott package

    We have implemented a functor based approach to translation in the translation package, used for nlp as well as serialization and parsing.

    The library package is contains basic structures implemented in HoTT.

    Definition Classes
    root
  • package learning
    Definition Classes
    provingground
  • object TruncatedFiniteDistribution extends Serializable
    Definition Classes
    learning
  • Geom

object Geom extends TruncatedFiniteDistribution[VarValueSet[FiniteDistribution]]

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  1. Geom
  2. TruncatedFiniteDistribution
  3. Serializable
  4. Product
  5. Equals
  6. GenTruncatedFiniteDistribution
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  1. final def !=(arg0: Any): Boolean
    Definition Classes
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  2. final def ##: Int
    Definition Classes
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  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
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  5. def clone(): AnyRef
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  6. final def eq(arg0: AnyRef): Boolean
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  7. final def getClass(): Class[_ <: AnyRef]
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  8. final def isInstanceOf[T0]: Boolean
    Definition Classes
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  9. def mapsSum[X, Y](first: Map[X, FiniteDistribution[Y]], second: Map[X, FiniteDistribution[Y]]): Map[X, FiniteDistribution[Y]]
  10. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. def nodeCoeffDist[Y](initState: VarValueSet[FiniteDistribution])(nodeCoeffs: NodeCoeffs[VarValueSet[FiniteDistribution], Double, HNil, Y], epsilon: Double): FiniteDistribution[Y]
  12. def nodeCoeffFamilyMap[Dom <: HList, Y](initState: VarValueSet[FiniteDistribution])(nodeCoeffs: NodeCoeffs[VarValueSet[FiniteDistribution], Double, Dom, Y], baseDist: FiniteDistribution[Dom], epsilon: Double): Map[Dom, FiniteDistribution[Y]]
  13. val nodeCoeffSeq: NodeCoeffSeq[VarValueSet[FiniteDistribution], Double]
    Definition Classes
    TruncatedFiniteDistribution
  14. def nodeDist[Y](initState: VarValueSet[FiniteDistribution])(generatorNode: GeneratorNode[Y], epsilon: Double): FiniteDistribution[Y]

    recursively determines the finite distribution given a generator node; the main work is done here

    recursively determines the finite distribution given a generator node; the main work is done here

    Y

    values of the corresponding random variable

    initState

    initial state

    generatorNode

    generator node to resolve

    epsilon

    cutoff

    returns

    distribution corresponding to the output random variable

    Definition Classes
    TruncatedFiniteDistributionGenTruncatedFiniteDistribution
  15. def nodeFamilyDist[Dom <: HList, Y](initState: VarValueSet[FiniteDistribution])(generatorNodeFamily: GeneratorNodeFamily[Dom, Y], baseDist: FiniteDistribution[Dom], epsilon: Double): Map[Dom, FiniteDistribution[Y]]
  16. final def notify(): Unit
    Definition Classes
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  17. final def notifyAll(): Unit
    Definition Classes
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    @native() @HotSpotIntrinsicCandidate()
  18. def productElementNames: Iterator[String]
    Definition Classes
    Product
  19. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  20. def updateAll(dataSeq: Seq[Value[_ <: HList, _, Double]]): TruncatedFiniteDistribution[VarValueSet[FiniteDistribution]]

    update coefficients, to be used in complex islands

    update coefficients, to be used in complex islands

    dataSeq

    the new coefficients

    returns

    TruncatedFiniteDistribution with updated coefficients

    Definition Classes
    TruncatedFiniteDistribution
  21. def varDist[Y](initState: VarValueSet[FiniteDistribution])(randomVar: RandomVar[Y], epsilon: Double): FiniteDistribution[Y]

    finite distribution for a random variable

    finite distribution for a random variable

    Y

    values of the random variable

    initState

    initial state

    randomVar

    random variable whose distribution is returned

    epsilon

    cutoff

    returns

    finite distribution for the given random variable

    Definition Classes
    GenTruncatedFiniteDistribution
  22. def varFamilyDist[RDom <: HList, Y](initState: VarValueSet[FiniteDistribution])(randomVarFmly: RandomVarFamily[RDom, Y], epsilon: Double): Map[RDom, FiniteDistribution[Y]]
  23. def varListDist[Dom <: HList](initState: VarValueSet[FiniteDistribution])(vl: RandomVarList[Dom], epsilon: Double): FiniteDistribution[Dom]

    finite distribution for a list of random variables

    finite distribution for a list of random variables

    Dom

    the HList giving the type of the variable list

    initState

    initial state

    vl

    list of random variables

    epsilon

    cutoff

    returns

    finite distribution of Dom

    Definition Classes
    GenTruncatedFiniteDistribution
  24. val varWeight: Double
    Definition Classes
    TruncatedFiniteDistribution
  25. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
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    @throws(classOf[java.lang.InterruptedException])
  26. final def wait(arg0: Long): Unit
    Definition Classes
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  27. final def wait(): Unit
    Definition Classes
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    @throws(classOf[java.lang.InterruptedException])

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  1. def finalize(): Unit
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