Modern applications of machine learning in quantum sciences

Understand

In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences.

• We cover the use of deep learning and kernel methods in supervised, unsupervised, and reinforcement learning algorithms for phase classification, representation of many-body quantum states, quantum feedback control, and quantum circuits optimization.
• Moreover, we introduce and discuss more specialized topics such as differentiable programming, generative models, statistical approach to machine learning, and quantum machine learning.