C-MI-GAN: Estimation of conditional mutual information using minmax formulation
A Mondal, A Bhattacharjee… - … on Uncertainty in …, 2020 - proceedings.mlr.press
Estimation of information theoretic quantities such as mutual information and its conditional
variant has drawn interest in recent times owing to their multifaceted applications. Newly …
variant has drawn interest in recent times owing to their multifaceted applications. Newly …
Diffeomorphic information neural estimation
Abstract Mutual Information (MI) and Conditional Mutual Information (CMI) are multi-purpose
tools from information theory that are able to naturally measure the statistical dependencies …
tools from information theory that are able to naturally measure the statistical dependencies …
CCMI: Classifier based conditional mutual information estimation
S Mukherjee, H Asnani… - Uncertainty in artificial …, 2020 - proceedings.mlr.press
Abstract Conditional Mutual Information (CMI) is a measure of conditional dependence
between random variables X and Y, given another random variable Z. It can be used to …
between random variables X and Y, given another random variable Z. It can be used to …
Understanding the limitations of variational mutual information estimators
Variational approaches based on neural networks are showing promise for estimating
mutual information (MI) between high dimensional variables. However, they can be difficult …
mutual information (MI) between high dimensional variables. However, they can be difficult …
Data-efficient mutual information neural estimator
Measuring Mutual Information (MI) between high-dimensional, continuous, random
variables from observed samples has wide theoretical and practical applications. Recent …
variables from observed samples has wide theoretical and practical applications. Recent …
Demi: Discriminative estimator of mutual information
Estimating mutual information between continuous random variables is often intractable and
extremely challenging for high-dimensional data. Recent progress has leveraged neural …
extremely challenging for high-dimensional data. Recent progress has leveraged neural …
Neural estimators for conditional mutual information using nearest neighbors sampling
S Molavipour, G Bassi… - IEEE transactions on signal …, 2021 - ieeexplore.ieee.org
The estimation of mutual information (MI) or conditional mutual information (CMI) from a set
of samples is a longstanding problem. A recent line of work in this area has leveraged the …
of samples is a longstanding problem. A recent line of work in this area has leveraged the …
Smoothed noise contrastive mutual information neural estimation
Abstract Information Noise Contrastive Estimation (InfoNCE) is a popular neural estimator of
mutual information (MI). While InfoNCE has demonstrated impressive results in …
mutual information (MI). While InfoNCE has demonstrated impressive results in …
Beyond normal: On the evaluation of mutual information estimators
Mutual information is a general statistical dependency measure which has found
applications in representation learning, causality, domain generalization and computational …
applications in representation learning, causality, domain generalization and computational …
Tight mutual information estimation with contrastive fenchel-legendre optimization
Abstract Successful applications of InfoNCE (Information Noise-Contrastive Estimation) and
its variants have popularized the use of contrastive variational mutual information (MI) …
its variants have popularized the use of contrastive variational mutual information (MI) …