American Institute of Physics

Algorithm optimizes machine learning techniques that use linear, tunable resistor networks

Framework applying Kirchoff’s laws of current flow and voltage changes across circuits can identify lower-energy analog ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Machine learning methods move self-driving labs closer to materials discovery at scale

Machine learning doesn't replace human intelligence, but it can outlast human endurance, which makes it a helpful tool for ...
Semiconductor Engineering

Machine Learning-Based IR Drop Prediction Approach

A new technical paper titled “Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate” was published by researchers at KTH Royal Institute of Technology and ...
Scientific American magazine

Nobel Prize in Physics Awarded for Breakthroughs in Machine Learning

The human brain, with its billions of interconnected neurons giving rise to consciousness, is generally considered the most powerful and flexible computer in the known universe. Yet for decades ...

How a study of pandemic-era tweets shaped Shahana Nandy's approach to machine learning

Although the domains she has explored range from mental health and healthcare to questions of equity, a common thread runs through each of them.
quantamagazine.org

What Is Machine Learning?

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...