I will talk about quantum recurrent neural networks based on quantum dissipative neural networks (DQNNs), which use quantum neural networks to describe general causal quantum automata. I will first introduce feed-forward DQNNs and then go to the recurrent case. After discussing the architecture and universality, I will discuss training algorithms and numerical results showing good generalisation behaviour.
