Inspired by the coattention mechanism , we propose an attention-based inferer (ABI) to estimate the mean and standard deviation of a distribution belongs to p θ (•) or q φ (•) by capturing semantic interactions of input sequences.
vari-ational Autoencoder (vAE) based models have shown great potential in modeling the one-tomany problem and generate diversified inferences (Bowman et al., 2015;Zhao et al., 2017).