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EPJ Data Science
Figure 2 | EPJ Data Science

Figure 2

From: Activism via attention: interpretable spatiotemporal learning to forecast protest activities

Figure 2

Overview of our proposed ActAttn architecture. It incorporates hierarchical attentional networks where the top level (a) differentiates the intra-region and inter-region importance, and the second level (b) identifies the hub regions. The temporal dependency of time-varying features in both intra- and inter-regions are modeled using LSTM (c), with sparse feature learning using Group Lasso (d)

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