Application of machine learning methods in quantum many-body physics

Machine learning methods have attracted considerable interest in various fields.In this paper we review recent progress in the application of machine learning methods to quantum many-body physics. Special attention is devoted to the potential relation between the "exponential wall" difficulties in this field of physics and machine learning methods. We also discuss the possibility that progress in quantum many-body physics will also be beneficial to the machine learning community.