A new review in Nature chronicles the many ways machine learning is popping up in particle physics research. Experiments at the Large Hadron Collider produce about a million gigabytes of data every ...

Scientists used a neural network, a type of brain-inspired machine learning algorithm, to sift through large volumes of particle collision data. Particle physicists are tasked with mining this massive ...

Scientists have developed a new machine-learning platform that makes the algorithms that control particle beams and lasers smarter than ever before. Their work could help lead to the development of ...

In many scientific fields which rely on statistical inference, simulations are often used to map from theoretical models to experimental data, allowing scientists to test model predictions against ...

The volume of data particle physicists have to sort through at the Large Hadron Collider is staggering, and it’s about to increase by an order of magnitude. To cope with this torrent of data, CERN is ...

Operators of the primary particle accelerator at the U.S. Department of Energy's Thomas Jefferson National Accelerator Facility are getting a new tool to help them quickly address issues that can ...

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the aging global population, AD incidence and its ...

There have been many attempts at teaching robots how to grab delicate objects, but they tend to rely on rough approximations that quickly fall apart in real life. MIT researchers may have a better ...

Operators of Jefferson Lab's primary particle accelerator are getting a new tool to help them quickly address issues that can prevent it from running smoothly. The machine learning system has passed ...