We use a neural network which consists of a weight matrix W 1 ∈ R d×d for left children and a weight matrix W 2 ∈ R d×d for right children to compute the vector for a parent node in a bottom up manner.
the complexities of the two models are dominated by the matrix-vector multiplications that are carried out.