The Kavli Institute for Theoretical Sciences at the University of Chinese Acadamy of Sciences presents "Machine Learning and Many-Body Physics", a summer school and workshop.
The central questions addressed in this workshop are "How is machine learning useful for physics/chemistry ?" and "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