In recent years the dramatic progress in machine learning has begun to impact many areas
of science and technology significantly. In the present perspective article, we explore how …

Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …

The power of quantum computing technologies is based on the fundamentals of quantum
mechanics, such as quantum superposition, quantum entanglement, or the no-cloning …

Quantum information technologies, on the one hand, and intelligent learning systems, on the
other, are both emergent technologies that are likely to have a transformative impact on our …

Model bias is an inherent limitation of the current dominant approach to optimal quantum
control, which relies on a system simulation for optimization of control policies. To overcome …

Emerging reinforcement learning techniques using deep neural networks have shown great
promise in control optimization. They harness non-local regularities of noisy control …

The development of estimation and control theories for quantum systems is a fundamental
task for practical quantum technology. This vision article presents a brief introduction to …

The ability to prepare a physical system in a desired quantum state is central to many areas
of physics such as nuclear magnetic resonance, cold atoms, and quantum computing. Yet …

Recently, a state-of-the-art algorithm, called deep deterministic policy gradient (DDPG), has
achieved good performance in many continuous control tasks in the MuJoCo simulator. To …

Machine learning with artificial neural networks is revolutionizing science. The most
advanced challenges require discovering answers autonomously. In the domain of …