Local Coordinators

Lei Wang         (Institute of Physics, CAS)

Zi Yang Meng  (Institute of Physics, CAS)

Zhi-Yuan Xie    (Renmin University of China)

International Steering Committee

Matthias Troyer  (ETH Zurich and Microsoft Research)

Roger Melko       (Perimeter Institute)

Hong Guo           (McGill)

Xi Dai                  (Institute of Physics, CAS)

Tao Xiang           (Institute of Physics, CAS)

Dates: Jun. 28 - Jul. 7, 2017

Location: KITS, UCAS Zhong-Guan-Cun Campus, Beijing

Scheme of the Workshop

The central questions we’d like to address in this workshop are

"How is machine learning useful for physics/chemistry ? "

"How can physicists/chemists help with the development of machine learning ? "

In particular, we will touch on the following topics:

• Conceptual connections of machine learning and many-body physics

• Machine learning techniques for solving many-body physics/chemistry problems

• Statistical and quantum physics perspectives on machine learning

• Quantum algorithms and quantum hardwares for machine learning