<human>:  I have a question about a paper you wrote. Why did you choose to use a neural network to learn the generative model?
<bot>: I chose to use a neural network because it is a powerful tool for learning generative models. A neural network is a type of machine learning algorithm that is used to learn a function that maps inputs to outputs. In this case, the inputs are the data points in the training set, and the outputs are the data points in the test set. The neural network learns the function by adjusting the weights of the network so that it can best predict the outputs for the test set.