We assume the approximation has the following form: where: the mean µ and standard variance σ are the outputs of the neural network based on the representations of h D and h Y .
the BiLStM consists of forward and backward LStMs, which read the sequence from left-toright and right-to-left to produce both forward and backward sequence of hidden states ( , and the VDANLG architecture which consists of two main components: the VRALStM to generate the sentence and two Critics with an adversarial training procedure to guide the model in domain adaptation.