Revealing the dynamics of neural information processing with multivariate information decomposition
The varied cognitive abilities and rich adaptive behaviors enabled by the animal nervous
system are often described in terms of information processing. This framing raises the issue …
system are often described in terms of information processing. This framing raises the issue …
Quantifying & modeling multimodal interactions: An information decomposition framework
The recent explosion of interest in multimodal applications has resulted in a wide selection
of datasets and methods for representing and integrating information from different …
of datasets and methods for representing and integrating information from different …
A review of partial information decomposition in algorithmic fairness and explainability
Partial Information Decomposition (PID) is a body of work within information theory that
allows one to quantify the information that several random variables provide about another …
allows one to quantify the information that several random variables provide about another …
Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks
Striking progress has been made in understanding cognition by analyzing how the brain is
engaged in different modes of information processing. For instance, so-called synergistic …
engaged in different modes of information processing. For instance, so-called synergistic …
Gaussian partial information decomposition: Bias correction and application to high-dimensional data
P Venkatesh, C Bennett, S Gale… - Advances in …, 2024 - proceedings.neurips.cc
Recent advances in neuroscientific experimental techniques have enabled us to
simultaneously record the activity of thousands of neurons across multiple brain regions …
simultaneously record the activity of thousands of neurons across multiple brain regions …
Demystifying local and global fairness trade-offs in federated learning using partial information decomposition
In this paper, we present an information-theoretic perspective to group fairness trade-offs in
federated learning (FL) with respect to sensitive attributes, such as gender, race, etc …
federated learning (FL) with respect to sensitive attributes, such as gender, race, etc …
Partial information decomposition for continuous variables based on shared exclusions: Analytical formulation and estimation
Describing statistical dependencies is foundational to empirical scientific research. For
uncovering intricate and possibly nonlinear dependencies between a single target variable …
uncovering intricate and possibly nonlinear dependencies between a single target variable …
A partial information decomposition for discrete and continuous variables
K Schick-Poland, A Makkeh, AJ Gutknecht… - arXiv preprint arXiv …, 2021 - arxiv.org
Conceptually, partial information decomposition (PID) is concerned with separating the
information contributions several sources hold about a certain target by decomposing the …
information contributions several sources hold about a certain target by decomposing the …
Dynamical independence: discovering emergent macroscopic processes in complex dynamical systems
We introduce a notion of emergence for macroscopic variables associated with highly
multivariate microscopic dynamical processes. Dynamical independence instantiates the …
multivariate microscopic dynamical processes. Dynamical independence instantiates the …
Disentanglement analysis with partial information decomposition
We propose a framework to analyze how multivariate representations disentangle ground-
truth generative factors. A quantitative analysis of disentanglement has been based on …
truth generative factors. A quantitative analysis of disentanglement has been based on …