Figure 5From: Time-varying graph representation learning via higher-order skip-gram with negative samplingTwo-dimensional projections of the 128-dim embedding manifold spanned by dynamic node embeddings for LyonSchool data learned with baseline methods. As in Fig. 4 we highlight the temporal participation to communities (top of each panel) and the time interval of activation (bottom of each panel)Back to article page