Jul 8, 2014 · We propose an information-theoretic approach, based on the insight that conditions on entropies of Bayesian networks take the form of simple linear ...

One of the goals of probabilistic inference is to decide whether an empirically observed distribution is compatible with a candidate. Bayesian network.

Jul 23, 2014 · We describe an algorithm for deriving entropic tests for latent structures. The well-known conditional independence tests appear as a special ...

Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and ...

Title: Inferring latent structures via information inequalities. Authors: R. Chaves, L. Luft, T. O. Maciel, D. Gross, D. Janzing, B. Schölkopf. Comments: 10 ...

Inferring latent structures via information inequalities. R. Chaves, L. Luft, T. O. Maciel, D. Gross, D. Janzing, B. Schölkopf Proceedings of the 30th ...

We study the problem of discovering the simplest latent variable that can make two observed discrete variables conditionally independent.

Jan 6, 2015 · A quantum causal structure specifies the functional dependency between a collection of quantum systems and classical variables.

We describe a methodology for making counterfactual predictions in settings where the information held by strategic agents is unknown.

Application areas include gene regulation graph inference in Biology. (using gene expression data), as well as spectroscopy, climate studies, functional.