To effectively map local features of tiles to the corresponding adjacency matrix, a graph neural network is employed. This trained model is used to predict short violations at the placement stage.

Learning the gene coexpression pattern is a central challenge for high-dimensional gene expression analysis. Recently, sparse singular value decomposition (SVD) has been used to achieve this goal.