Optimization lies at the core of both quantum physics and machine learning. By combining them, the authors introduce a method which uses classical generative models for variational optimization. This method is shown to provide fast training convergence and generate diverse, nearly optimal solutions for a wide range of quantum tasks.
- Lingxia Zhang
- Xiaodie Lin
- Zizhu Wang
