Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, molecules, and materials.

In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is revolutionizing our understanding of brain aging at an unprecedented cellular ...

This interpretable machine learning-based approach paves the way for multimodal experiments that can validate or disprove the accuracy of different brain network models. Learning Objectives: 1. Define ...

Researchers have developed a technique that significantly improves the performance of large language models without ...

A new machine learning approach identifies cellular senescence at single-cell resolution across varying cell types and tissue ...

To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...

In this letter, we consider the concept of mobile crowd-machine learning (MCML) for a federated learning model. The MCML enables mobile devices in a mobile network to collaboratively train neural ...