An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...
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 ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results