 Indian buffet process

The Indian Buffet Process is a concept in Bayesian nonparametrics, introduced by the statisticians Teh, Griffiths, G, and others in a series of seminal papers. It is a stochastic process that allows for the flexible modeling of data with an unknown number of underlying groups or clusters, making it particularly useful in situations where the number of clusters is not predetermined.