Models use distributions to represent uncertainty, define likelihood-based losses, and sample outputs. A valid discrete distribution sums to one, while a continuous distribution integrates to one over its domain.
A probability distribution assigns probabilities or probability density to possible outcomes.
Models use distributions to represent uncertainty, define likelihood-based losses, and sample outputs. A valid discrete distribution sums to one, while a continuous distribution integrates to one over its domain.