To fully characterize the information that two source variables carry about a third target
variable, one must decompose the total information into redundant, unique, and synergistic …

We consider the “partial information decomposition”(PID) problem, which aims to
decompose the information that a set of source random variables provide about a target …

Partial information decomposition of the multivariate mutual information describes the
distinct ways in which a set of source variables contains information about a target variable …

The integration and transfer of information from multiple sources to multiple targets is a core
motive of neural systems. The emerging field of partial information decomposition (PID) …

The entropy of a pair of random variables is commonly depicted using a Venn diagram. This
representation is potentially misleading, however, since the multivariate mutual information …

The partial information decomposition (PID) is a promising framework for decomposing a
joint random variable into the amount of influence each source variable X i has on a target …

The partial information decomposition (PID) framework is concerned with decomposing the
information that a set of (two or more) random variables (the sources) has about another …

Complex systems arise as a result of interdependences between multiple variables, whose
causal interactions can be visualized in a time-series graph. Transfer entropy and …

Intuitively, the level of autonomy of an agent is related to the degree to which the agent's
goals and behaviour are decoupled from the immediate control by the environment. Here …

Understanding how different information sources together transmit information is crucial in
many domains. For example, understanding the neural code requires characterizing how …