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surprisal's Usage Examples:

Simplicity versus likelihood in visual perception: From surprisals to precisals.

If the surprisal of catching a disease without it is 16 bits, but the surprisal of harm from.

as information content or surprisal, the support (log-likelihood) of a model, given an event, is the negative of the surprisal of the event, given the model:.

In the surprisal theory, the cost of processing.

derived a measure of information content called the self-information or "surprisal" of a message m {\displaystyle m} : I ⁡ ( m ) log ⁡ ( 1 p ( m ) ) .

maximum likelihood estimate (MLE) maximizes likelihood (minimizes expected surprisal), which can be interpreted geometrically by using entropy to measure variation:.

Another account is that the N400 reflects prediction error or surprisal.

The surprisal theory is a theory of sentence processing based on information theory.

divergence is the (objective) expected value of Bob"s (subjective) surprisal minus Alice"s surprisal, measured in bits if the log is in base 2.

Word-based surprisal was a strong predictor of N400 amplitude in an ERP corpus.

The information content (also called the surprisal) of an event E {\displaystyle E} is a function which decreases as the.

imagine that the surprisal of harm from a vaccination is 20 bits.

In information theory, the information content, self-information, surprisal, or Shannon information is a basic quantity derived from the probability of.

Synonyms:

perturbation, surprise, disruption,

Antonyms:

inactivity, composure, refrain, defend,