Theoretical Physics for Machine Learning

Aspen Center For Physics 

Winter Conference

February 26 - March 3, 2023 

Machine learning is undergoing a scientific revolution, with a succession of experimental triumphs. These empirical successes have often led to, and sometimes been inspired by, improved theoretical understanding that leans heavily on insight from physics. This Aspen Winter Conference will investigate the use of ideas from theoretical physics --- in particular, high energy theory, condensed matter theory, and statistical mechanics --- to better understand machine learning. We will bring together researchers from the theoretical physics and machine learning communities to discuss the physics of ML, with an eye towards both improved performance and progress on new challenges.

For the 2019 version of this conference, see here

For questions, please contact us.

Scientific Organizing Committee

Adam Brown

Ethan Dyer

Paul Ginsparg

Guy Gur-Ari

Maithra Raghu