Physics ∩ ML

Physics ∩ ML


The goal of PhysicsML (read ‘Physics Meets ML’) is to bring together researchers from machine learning and physics to learn from each other and push research forward together. In this inaugural edition, we will especially highlight some amazing progress made in string theory with machine learning and in the understanding of deep learning from a physical angle. Nevertheless, we invite a cast with wide ranging expertise in order to spark new ideas. Plenary sessions from experts in each field and shorter specialized talks will introduce existing research. We will hold moderated discussions and breakout groups in which participants can identify problems and hopefully begin new collaborations in both directions. For example, physical insights can motivate advanced algorithms in machine learning, and analysis of geometric and topological datasets with machine learning can yield critical new insights in fundamental physics.

Please contact an organizing member if you wish to participate in this workshop.


Greg Yang, Microsoft Research
Jim Halverson, Northeastern University
Sven Krippendorf, LMU Munich
Fabian Ruehle, CERN, Oxford University
Rak-Kyeong Seong, Samsung SDS
Gary Shiu, University of Wisconsin

Microsoft Advisers

Chris Bishop, Microsoft Research
Jennifer Chayes, Microsoft Research
Michael Freedman, Microsoft Research
Paul Smolensky, Microsoft Research


Thursday, April 25, 2019

Session 1

Plenary talks

8:00 AM-9:00 AM Breakfast
9:00 AM-9:45 AM Physics insights in deep learning algorithms | Taco Cohen
9:45 AM-10:30 AM Physical insights in understanding deep learning | Jascha Sohl-Dickstein
10:30 AM-11:00 AM Coffee Break
11:00 AM-11:45 AM ML applied to string theory | Mike Douglas
11:45 AM-12:30 PM ML applied to condensed matter | Koji Hashimoto
12:30 PM-2:00 PM Lunch

Session 2

Applying physical insights to ML

2:00 PM-2:45 PM Plenary | Pratik Chaudhari
2:45 PM-4:05 PM Short talks – 4 x 20 minute blocks, as follows:
3 talks, 5 minutes each
5 minute Q&A
4:05 PM-4:30 PM Coffee Break
4:30 PM-5:30 PM Discussion

Friday, April 26, 2019

Session 3

Applying ML to physics

8:00 AM-9:00 AM Breakfast
9:00 AM-9:45 AM Plenary | Liam McAllister
9:45 AM-10:15 AM Coffee Break
10:15 AM-11:35 AM Short talks – 4 x 20 minute blocks, as follows:
3 talks, 5 minutes each
5 minute Q&A
11:35 AM-12:30 PM Discussion
12:30 PM-2:00 PM Lunch

Session 4

Breakout groups

2:00 PM-5:00 PM