It is well-known that estimation of the directed dependency between high-dimensional data sequences suffers from the "curse of dimensionality" problem.

In this paper, we propose a new NUE procedure, hereinafter will be referred to as mean of the squared residual (MSR)- based NUE, which uses MSR of the NN-based ...

It is well-known that estimation of the directed dependency between high-dimensional data sequences suffers from the “curse of dimensionality” problem.

It is well-known that estimation of the directed dependency between high-dimensional data sequences suffers from the "curse of dimensionality" problem.

TL;DR: In this paper, a progressive input variable selection technique was proposed to reduce the dimensionality of the data, and thereby improve the ...

We propose a new estimator to measure directed dependencies in time series. The dimensionality of data is first reduced using a new non-uniform embedding ...

Nov 27, 2020 · We propose a new estimator to measure directed dependencies in time series. The dimensionality of data is first reduced using a new non-uniform embedding ...

This paper shows that the neural estimator for conditional mutual information is consistent when the dataset is generated with samples of a stationary and ...

Aug 30, 2024 · Estimation of Directed Dependencies in Time Series Using Conditional Mutual Information and Non-linear Prediction-conference_proceeding.

Sep 12, 2024 · We propose a new estimator to measure directed dependencies in time series. The dimensionality of data is first reduced using a new ...