Frontiers

AI & Mechanistic Neuroscience: Hybrid Models Beyond Prediction

The intersection of artificial intelligence and mechanistic neuroscience is rapidly transforming our understanding of neural systems. While AI ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
IEEE

Frequency Response Estimation via Multi-Coefficient Surrogate Models of Rational Complex Functions

Abstract: Accurate frequency response estimation is crucial in various engineering applications, including electrical circuits especially compact power electronic circuits. In EMC, numerical ...
IEEE

A Self-Supervised Framework for Multi-Function Radar Signal Sequence Prediction

Abstract: Predicting multi-function radar (MFR) signal sequences is essential for radar signal analysis. Traditional methods often face challenges due to noise and outliers in intercepted signal ...
GitHub

STAR: Similarity-guided Teacher-Assisted Refinement for Super-Tiny Function Calling Models

This repository contains the code and instructions necessary to reproduce the experiments presented in the paper: "STAR: Similarity-guided Teacher-Assisted Refinement for Super-Tiny Function Calling ...