concept
active
concept:categorical-distribution

Categorical Distribution

Probability distribution over discrete states or outcomes.

Neighborhood — ranked by edge-count

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

  • In active inference, the distribution over goal states; here replaced by the learned self-prior rather than a hand-specified prior
  • The distribution of latent representations produced by the model under unperturbed inputs
  • Categorical VAEmethod0.763
    Used as the observation encoder/decoder for compressing visual and proprioceptive inputs into discrete latent states
  • Conjugate prior for categorical variables; used for beliefs about likelihood matrix A.
  • Category Theoryconcept0.738
    Fundamental mathematical tool; poset-as-category provides simple instances of categorical notions like products and adjunctions.
  • probabilityconcept0.731
    Measure of expected sensory input, core to linking value and surprise.
  • Generalizationconcept0.727
    Ability to apply learned solutions to novel circumstances.
  • hierarchyconcept0.719
    An ordering of texts via spatial cues like indentation, size, and placement, implying importance.