Abstract: In various applications, the importance of localization has increased significantly. In this study, we propose a method combining a filter bank and kernel density estimation (KDE) for robust ...

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 ...

Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...

NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...

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 ...

This sample project shows how a Python application can be configured to send Semantic Kernel telemetry to the Application Performance Management (APM) vendors of your choice. In this sample, we ...

Abstract: In manufacturing and logistics, various applications exploiting IoT devices are started to be used. Although there is a demand for wireless connection between the IoT devices to networks, ...

Modeling periodic phenomena with accuracy is a key aspect to detect abnormal behavior in time series for the context of Structural Health Monitoring. Modeling complex non-harmonic periodic pattern ...