Mutual Information Estimation

37 papers with code • 0 benchmarks • 0 datasets

To estimate mutual information from samples, specially for high-dimensional variables.

Latest papers with no code

Artifact Feature Purification for Cross-domain Detection of AI-generated Images

no code yet • 17 Mar 2024

We also find that the artifact features APN focuses on across generators and scenes are global and diverse.

Mutual Information Estimation via Normalizing Flows

no code yet • 4 Mar 2024

We propose a novel approach to the problem of mutual information (MI) estimation via introducing normalizing flows-based estimator.

On regularized Radon-Nikodym differentiation

no code yet • 15 Aug 2023

We discuss the problem of estimating Radon-Nikodym derivatives.

Subgraph Networks Based Contrastive Learning

no code yet • 6 Jun 2023

In addition, we also investigate the impact of the second-order subgraph augmentation on mining graph structure interactions, and further, propose a contrastive objective that fuses the first-order and second-order subgraph information.

On the Effectiveness of Hybrid Mutual Information Estimation

no code yet • 1 Jun 2023

Estimating the mutual information from samples from a joint distribution is a challenging problem in both science and engineering.

Computing high-dimensional optimal transport by flow neural networks

no code yet • 19 May 2023

Flow-based models are widely used in generative tasks, including normalizing flow, where a neural network transports from a data distribution $P$ to a normal distribution.

Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression

no code yet • 1 May 2023

We show that if these auxiliary densities are constructed such that they overlap with $p$ and $q$, then a multi-class logistic regression allows for estimating $\log p/q$ on the domain of any of the $K+2$ distributions and resolves the distribution shift problems of the current state-of-the-art methods.

Copula Density Neural Estimation

no code yet • 25 Nov 2022

Probability density estimation from observed data constitutes a central task in statistics.

Representation Learning with Information Theory for COVID-19 Detection

no code yet • 4 Jul 2022

Successful data representation is a fundamental factor in machine learning based medical imaging analysis.