package infer

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Type Members

  1. class AssignmentSummary extends Summary

    A Summary with all its probability on one variable-value Assignment.

  2. class BPEdge extends AnyRef

    A dumb container for messages factor->variable and variable->factor

  3. trait BPFactor extends FactorMarginal

  4. abstract class BPFactor1 extends SimpleDiscreteMarginal1[DiscreteVar] with BPFactor

  5. class BPFactor1Factor1 extends BPFactor1 with DiscreteMarginal1[DiscreteVar] with DiscreteMarginal1Factor1[DiscreteVar]

  6. class BPFactor1Factor2 extends BPFactor1 with DiscreteMarginal1[DiscreteVar] with DiscreteMarginal1Factor2[DiscreteVar, VectorVar]

  7. class BPFactor1Factor2Left extends BPFactor1 with DiscreteMarginal1[DiscreteVar] with DiscreteMarginal1Factor2Other[VectorVar, DiscreteVar]

  8. class BPFactor1Factor3 extends BPFactor1 with DiscreteMarginal1Factor3[VectorVar, VectorVar, VectorVar, DiscreteVar]

  9. abstract class BPFactor2 extends DiscreteMarginal2[DiscreteVar, DiscreteVar] with BPFactor

  10. class BPFactor2Factor2 extends BPFactor2 with DiscreteMarginal2Factor2[DiscreteVar, DiscreteVar]

  11. class BPFactor2Factor3 extends BPFactor2 with DiscreteMarginal2Factor3[DiscreteVar, DiscreteVar, VectorVar]

  12. class BPFactor3Factor3 extends DiscreteMarginal3[DiscreteVar, DiscreteVar, DiscreteVar] with BPFactor with DiscreteMarginal3Factor3[DiscreteVar, DiscreteVar, DiscreteVar]

  13. class BPFactor4Factor4 extends DiscreteMarginal4[DiscreteVar, DiscreteVar, DiscreteVar, DiscreteVar] with BPFactor with DiscreteMarginal4Factor4[DiscreteVar, DiscreteVar, DiscreteVar, DiscreteVar]

  14. trait BPRing extends AnyRef

  15. class BPSummary extends Summary

    A collection of marginals inferred by belief propagation.

  16. trait BPVariable extends AnyRef

  17. class BPVariable1 extends DiscreteMarginal1[DiscreteVar] with BPVariable

  18. trait DiscreteMarginal extends Marginal

    A Marginal in which all the variables are discrete (either singleton or tensors).

  19. trait DiscreteMarginal1[V1 <: VectorVar] extends Marginal1 with DiscreteMarginal

  20. trait DiscreteMarginal1Factor1[V1 <: VectorVar] extends FactorMarginal

  21. trait DiscreteMarginal1Factor2[V1 <: VectorVar, V2 <: VectorVar] extends FactorMarginal

  22. trait DiscreteMarginal1Factor2Other[V1 <: VectorVar, V2 <: VectorVar] extends FactorMarginal

  23. trait DiscreteMarginal1Factor3[V1 <: VectorVar, V2 <: VectorVar, V3 <: VectorVar, V4 <: DiscreteVar] extends FactorMarginal

  24. class DiscreteMarginal2[V1 <: VectorVar, V2 <: VectorVar] extends DiscreteMarginal with Marginal2

  25. trait DiscreteMarginal2Factor2[V1 <: VectorVar, V2 <: VectorVar] extends DiscreteMarginal2[V1, V2] with FactorMarginal

  26. trait DiscreteMarginal2Factor3[V1 <: VectorVar, V2 <: VectorVar, V3 <: VectorVar] extends FactorMarginal

  27. class DiscreteMarginal3[V1 <: VectorVar, V2 <: VectorVar, V3 <: VectorVar] extends DiscreteMarginal

  28. trait DiscreteMarginal3Factor3[V1 <: VectorVar, V2 <: VectorVar, V3 <: VectorVar] extends FactorMarginal

  29. class DiscreteMarginal4[V1 <: VectorVar, V2 <: VectorVar, V3 <: VectorVar, V4 <: VectorVar] extends DiscreteMarginal

  30. trait DiscreteMarginal4Factor4[V1 <: VectorVar, V2 <: VectorVar, V3 <: VectorVar, V4 <: VectorVar] extends FactorMarginal

  31. class DiscreteMeanField extends MeanField

    Performs naive mean field inference with a Q Summary that is a set of independent Discrete distributions

  32. class DiscreteProposalMaximizer extends DiscreteProposalSampler

  33. class DiscreteProposalSampler extends ProposalSampler[DiscreteVar]

    A proposal sampler that considers each of the values of a DiscreteVar and scores them efficiently by unrolling factors from the Model just once.

  34. class DiscreteSeqMarginal[V <: DiscreteSeqVariable] extends Marginal1

  35. class DiscreteSummary1[V <: DiscreteVar] extends IncrementableSummary

    A summary with a separate Proportions distribution for each of its DiscreteVars

  36. class DualDecomposition extends util.GlobalLogging

  37. trait FactorMarginal extends AnyRef

    A Marginal associated with a Factor.

  38. trait FactorQueue[C] extends Sampler[C]

    Manage and use a queue to more often revisit low-scoring factors and re-sample their variables.

  39. class GibbsSampler extends ProposalSampler[Var]

    Sample a value for a single variable.

  40. trait GibbsSamplerClosure extends AnyRef

  41. trait GibbsSamplerHandler extends AnyRef

  42. trait IncrementableSummary extends Summary

    A Summary that can be used to gather weighted samples into its Marginals.

  43. trait Infer[-A <: Iterable[variable.Var], -B <: model.Model] extends AnyRef

  44. trait InferByBP extends Infer[Iterable[DiscreteVar], model.Model]

  45. class InferByGibbsSampling extends Infer[Iterable[MutableDiscreteVar], model.Model]

  46. class InferBySampling[C] extends AnyRef

  47. class IteratedConditionalModes extends SettingsMaximizer[Var with IterableSettings]

    Besag's Iterated Conditional Modes.

  48. class LoopyBPSummary extends BPSummary

  49. class LoopyBPSummaryMaxProduct extends BPSummary

  50. class MAPSummary extends Summary

    A Summary with all its probability on one variable-value Assignment, and which can also be used for learning because it includes factors.

  51. abstract class MHSampler[C] extends ProposalSampler[C]

    A Metropolis-Hastings sampler.

  52. class MPLP extends util.GlobalLogging

    User: apassos Date: 5/29/13 Time: 8:46 AM

  53. trait Marginal extends AnyRef

    Stores a marginal distribution containing a joint distribution over a set of variables.

  54. trait Marginal1 extends Marginal

  55. trait Marginal2 extends Marginal

  56. trait Maximize[-A <: Iterable[variable.Var], -B <: model.Model] extends Infer[A, B]

    An inference engine that finds score-maximizing values.

  57. trait MaximizeByBP extends InferByBP with Maximize[Iterable[DiscreteVar], model.Model]

  58. class MaximizeByMPLP extends Maximize[Iterable[DiscreteVar], model.Model]

  59. class MaximizeSuite extends Maximize[Iterable[variable.Var], model.Model]

  60. trait MeanField extends AnyRef

    An inferencer for mean field inference.

  61. case class ModelWithInference[M, V](vars: V, model: M)(implicit infer: (V, M) ⇒ WarmStartWeightedSummary) extends Product with Serializable

  62. class MultivariateGaussianMarginal1[V1 <: MutableTensorVarTensor1] extends Marginal

  63. class ProportionsDirichletMarginal1[V <: ProportionsVar] extends Marginal

  64. class Proposal[C] extends AnyRef

    For storing one of the MCMC sampling proposals considered.

  65. trait ProposalSampler[C] extends Sampler[C]

    Samplers that generate a list of Proposal objects, and select one log-proportionally to their modelScore.

  66. class RealGaussianMarginal1[V1 <: RealVar] extends Marginal

  67. trait RealMarginal1[V1 <: RealVar] extends Marginal

  68. class RealSpikeMarginal1[V1 <: RealVar] extends AbstractAssignment1[V1] with Marginal

  69. trait Sampler[C] extends AnyRef

    Samplers that key off of particular contexts.

  70. class SamplingFactorMarginal extends FactorMarginal

  71. class SamplingInferencer[C, S <: IncrementableSummary] extends AnyRef

  72. class SamplingMaximizer[C] extends AnyRef

  73. class SamplingSummary extends Summary

  74. class SamplingVariableMarginal extends DiscreteMarginal1[MutableDiscreteVar]

  75. abstract class SettingsMaximizer[C] extends SettingsSampler[C]

    Instead of randomly sampling according to the distribution, always pick the setting with the maximum acceptanceScore.

  76. abstract class SettingsSampler[C] extends ProposalSampler[C]

    Tries each one of the settings in the Iterator provided by the abstract method "settings(C)", scores each, builds a distribution from the scores, and samples from it.

  77. class SimpleDiscreteMarginal1[V1 <: VectorVar] extends DiscreteMarginal1[V1]

  78. class SingletonSummary[M <: Marginal1] extends Summary

    A Summary containing only one Marginal.

  79. trait Summary extends AnyRef

    The result of inference: a collection of Marginal objects.

  80. class Summary1[V <: variable.Var, M <: Marginal1] extends Summary

    A Summary that contains multiple Marginals of type M, each a marginal distribution over a single variable.

  81. class VariableSettingsSampler[V <: Var with IterableSettings] extends SettingsSampler[V]

    Tries each one of the settings of the given variable, scores each, builds a distribution from the scores, and samples from it.

  82. class VariablesSettingsSampler[V <: Var with IterableSettings] extends SettingsSampler[Seq[V]]

  83. trait WarmStartWeightedSummary extends AnyRef

    User: apassos Date: 6/15/13 Time: 7:38 AM