Abstract: Noise in communication systems is interference factor that constrains radio modulation classification. To address the impact of interference on automatic modulation classification (AMC), we ...
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 ...
An image-only artificial intelligence (AI) model for predicting the five-year risk of breast cancer provided stronger and more precise risk stratification than breast density assessment, according to ...
According to OpenAI (@OpenAI), OpenAI has released GPT-OSS-Safeguard in research preview, introducing two open-weight reasoning models specifically designed for safety classification tasks. These AI ...
Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and ...
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 ...
Python has been the language of data science since before machine learning was trendy, and now you can use it for building AI agents, too. Get the scoop on the new Google Agent Development Kit and ...
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 ...
Formation density can reflect the pressure state and fluid migration of the reservoir, which is crucial for the re-development of depleted reservoirs. Although various prediction models have been ...
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