Data with an underlying graph structure (such as citation networks) can be better classified by taking into account the underlying graph connections within the data. I implemented two recent papers: Semi-supervised classification with graph convolutional networks by Kipf et al. and Revisiting semi-supervised learning with graph embedding by Yang et al. to compare how their performance compares with other methods in the literature.