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Figure 1 | EPJ Data Science

Figure 1

From: Predicting partially observed processes on temporal networks by Dynamics-Aware Node Embeddings (DyANE)

Figure 1

Modified supra-adjacency representation (dyn-supra). The top panel shows a toy example with a temporal network at four successive times. At each time t we show in bold the nodes of \(V_{t}\), i.e., the nodes with at least one temporal edge. This network is mapped to a static representation (bottom) where nodes are (node,time) pairs of the original network, keeping for each node of the original network only the times in which it is active. In this toy example, node i is active at times t and \(t+1\) so the corresponding active nodes are \((i,t_{i,1}=t)\), \((i,t_{i,2}=t+1)\); node j is active at times t, \(t+2\) and \(t+3\) so the corresponding active nodes are \((j,t_{j,1}=t)\), \((j,t_{j,2}=t+2)\), \((j,t_{j,3}=t+3)\); finally, node k is active at times \(t+1\), \(t+2\) and \(t+3\) so the corresponding active nodes are \((k,t_{k,1}=t+1)\), \((k,t_{k,2}=t+2)\), \((k,t_{k,3}=t+3)\)

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