Category
page 1Probabilistic models
n-gram
An '''n-gram' is a sequence of n adjacent symbols in a particular order. The symbols may be n'' adjacent letters (including punctuation marks and blanks), syllables, or rarely whole words found in a language dataset; or adjacent phonemes extracted from a speech-recording dataset, or adjacent base pairs extracted from a genome. They are collected from a text corpus or speech corpus.
generative model
model for randomly generating observable data in probability and statistics
Gutenberg–Richter law
in seismology
latent Dirichlet allocation
generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar
probabilistic context-free grammar
Grammar model in linguistics
mixture model
statistical concept
deep belief network
type of artificial neural network
probabilistic programming
programming paradigm designed to describe probabilistic models and then perform inference in those models
flow-based generative model
Used in machine learning
Pólya urn model
statistical model in mathematics
probabilistic automaton
generalization of the non-deterministic finite automaton
Bayesian approach to brain function
explaining the brain's abilities through statistical principles
Class membership probabilities
Machine learning problem
Probabilistic relevance model