Quantum neural networks

@inproceedings{Beer2022QuantumNN,
  title={Quantum neural networks},
  author={Kerstin Beer},
  year={2022}
}
This PhD thesis combines two of the most exciting research areas of the last decades: quantum computing and machine learning. We introduce dissipative quantum neural networks (DQNNs), which are designed for fully quantum learning tasks, are capable of universal quantum computation and have low memory requirements while training. These networks are optimised with training data pairs in form of input and desired output states and therefore can be used for characterising unknown or untrusted…