Abstract: This article investigates a novel robust Kalman filter (RKF) by incorporating kernel density estimation (KDE) in the Kalman filtering framework to address the disturbance of measurement ...
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 ...
There’s been great interest in what Mira Murati’s Thinking Machines Lab is building with its $2 billion in seed funding and the all-star team of former OpenAI researchers who have joined the lab. In a ...
Abstract: To effectively address the challenges of undersampling techniques when handling imbalanced data, a new undersampling ensemble learning algorithm based on Kernel Density Estimation (KDEE) is ...
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 ...
--lineage=NAME Specify lineage (optional) --outputdir=DIR Output directory (default: creates folder next to input file) --density-xlim=N Density plot X-axis limit (default: 1400) --neighbor-xlim=N ...
ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...
Traditional machine learning models for automatic information classification require retraining data for each task. Researchers have demonstrated that art data can be automatically classified with ...
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