CUED Publications database

The Infinite Latent Events Model

Wingate, D and Goodman, ND and Roy, DM and Tenenbaum, JB (2009) The Infinite Latent Events Model. Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009. pp. 607-614.

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We present the Infinite Latent Events Model, a nonparametric hierarchical Bayesian distribution over infinite dimensional Dynamic Bayesian Networks with binary state representations and noisy-OR-like transitions. The distribution can be used to learn structure in discrete timeseries data by simultaneously inferring a set of latent events, which events fired at each timestep, and how those events are causally linked. We illustrate the model on a sound factorization task, a network topology identification task, and a video game task.

Item Type: Article
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 15 Dec 2015 13:29
Last Modified: 18 Jan 2016 06:19