SI and machine learning

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it?

Physics may seem like its own world, but different sectors using machine learning are all part of the same universe. 

Scientists inside and outside of particle physics and astrophysics are leaning on AI for assistance with complex tasks.

In the coming weeks, Symmetry will explore the ways scientists are using artificial intelligence to advance particle physics and astrophysics—in a series of articles written and illustrated entirely by humans.

Wan-Lin Hu’s job is to improve the way people and artificial intelligence collaborate to run SLAC’s complex machines.

The software tool sorts through messy data to reveal what’s really going on with solar panels on cloudy and sunny days.

The research reveals the potential for machine learning in understanding the complex behavior of quantum materials.

Analyzing X-ray movies with computer vision reveals how nanoparticles in a lithium-ion battery electrode work.

The algorithm pairs machine-learning techniques with classical beam physics equations to avoid massive data crunching.

Presented by Axel Levy.

Public lecture presented by Axel Levy