The input to the Influence Generator is the r×n dimensional vector of topic distributions from previous r timestamps of a related text stream, i.e., θ T −r:T −1 (assuming T as the current timestamp).
there has been a surge of research interest in the use of neural network (NN) architectures for language modeling and automatic text generation in recent years (Dieng et al., 2016;Kiros et al., 2014;Kiddon et al., 2016;Ranzato et al., 2015).