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 ...
Objectives: To analyse stroke rate (SR) and stroke length (SL) combinations among elite swimmers to better understand stroke strategies across all race distances of freestyle events. Design: We ...
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 ...
Meta AI has released Llama Prompt Ops, a Python package designed to streamline the process of adapting prompts for Llama models. This open-source tool is built to help developers and researchers ...
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 ...
Large Language Models (LLMs) have demonstrated significant advancements in reasoning capabilities across diverse domains, including mathematics and science. However, improving these reasoning ...
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