Winter School

The aim of the Quantum Machine Learning (QML) Winter School is to introduce the attendees to the basic aspects of quantum machine learning, its different facets as well as the early applications reported so far. The oral contributions will be delivered by world experts in the field and will cover topics from the fundamental concepts of machine learning with quantum devices to the state of the art techniques, algorithms and hardwares used nowadays. The school topics will cover quantum machine learning both at theoretical and experimental level, discussing quantum devices implementing qubits with different platforms – from superconductors to neutral atoms, from photons to trapped ions. These topics will be addressed either in the form of lectures or research/industrial talks, together with the help of computer-aided hands-on tutorials.