Quantum machine learning

Quantum computers trigger a growing interest in the scientific community since they aim to solve highly complex problems in a reasonable time. This can be achieved by using qubits, equivalent of classical bits, obtained by the superposition and entanglement of two quantum states. Redefining the core of a computer system means that specific algorithms need to be looked out, to be exploited. How are those algorithms designed? Do we actually have quantum computers available?

For our very first event, we welcomed Arthur and Jonathan:

• Arthur Pesah was previously working at Xanadu and 1QBit. Arthur gave an introduction about quantum machine learning “beyond the hype”.
  The introduction is available here.
• Jonathan Foldager is a PhD student at CogSys, working on the implementation of quantum machine learning models. He will talk about ensemble learning and quantum approximate optimization algorithm.
  His talk is available here.