“Near-term enhancements of machine learning with quantum computing: hybrid neural networks”
March 24th at 2:00 pm CET
Quantum computing promises to enhance machine learning solutions in multiple ways. On the one hand, quantum hardware can be used as an accelerator for training; on the other hand, encoding data on a quantum system allows for new representations, leading to better quality models. The latter approach, in particular, can already be explored with today’s quantum computing resources. For example, in this workshop, Reply will explain how established neural network architectures can be extended to include quantum components and the advantages this hybrid approach brings. We will also show some feasible applications on currently available quantum devices and discuss what the future of hybrid neural networks holds.