Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...
InfoWorld

16 open source projects transforming AI and machine learning

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...
IEEE

Series Arc Fault Identification Based on a Novel Newton-Optimized Sparse Kernel Support Vector Machine

Abstract: Existing machine learning-based methods for series arc fault (SAF) identification still suffer from slow training speed when dealing with large-scale SAF datasets. For this reason, we ...
Hospital Healthcare Europe

Machine learning-assisted mapping of VT ablation targets: progress and potential

Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
Devdiscourse

AI-driven rainfall forecasting shows major gains in predicting flood-triggering storms

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
IEEE

Adaptive Kernel Optimization for Probabilistic Learning: Integrating Support Vector Machines with Gaussian Process Frameworks

Abstract: With its robust capabilities for non-linear regression and classification, kernel-based learning has emerged as a fundamental component of state-of-the-art machine learning approaches. In ...