AKDE provides an accurate, adaptive kernel density estimator based on the Gaussian Mixture Model for multidimensional data. This Python implementation includes automatic grid construction for ...

Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...

Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jctc.5c00129. Notes on the functional form of reorganization energy and ...

Set create_data and do_plotting to True and press play. Initiation is at the bottom of the script. Requires numpy, matplotlib, and scipy. adk_estimator: Contains the functions that does the adaptive ...

An intelligent power transducer plays an important role in the acquisition, monitoring, and control of data in power systems. A power transducer faces challenges of reduced measurement accuracy and ...

ABSTRACT: Singh, Gewali, and Khatiwada proposed a skewness measure for probability distributions called Area Skewness (AS), which has desirable properties but has not been widely applied in practice.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph neural networks (GNNs) have been shown to be astonishingly capable models for ...

Density estimation methods often involve kernels, but there are advantages to using splines. Especially if the shape of the density is known to be decreasing, or unimodal, or bimodal, or if the ...