text: This paper draws an interesting connection between deep neural networks and theories of quantum entanglement. They leveraged the tool for analyzing quantum entanglement to deep neural networks, and proposed a graph theoretical analysis for neural networks. They demonstrated how their theory can help designing neural network architectures on the MNIST dataset. I think the theoretical findings are novel and may contribute to the important problem on understanding neural networks theoretically. I am not familiar with the theory for quantum entanglement though.