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Figure 1: The EnergyVis user interface, with multiple coordinated views. (A) The Model Energy Profile View allows users to select an energy profile of pre-loaded models, generate new profiles (for models that a user wishes to train), and import saved profiles. (B) The Consumption Chart allows users to view the energy and carbon consumption of their selected model. (C) Using the Model Region view, users can view the region where a model was trained, and select regions with a lower energy intensity as an alternative to reduce emissions. (D) Users can expand the Colored Equations for succinct descriptions of various variables and how they contribute to calculating a model's emissions. (E) Finally, users can view or adjust hardware used to train a model using Alternative Hardware.

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The study of network robustness is a critical tool in the characterization and sense making of complex interconnected systems such as infrastructure, communication and social networks. While significant research has been conducted in all of these areas, gaps in the surveying literature still exist. Answers to key questions are currently scattered across multiple scientific fields and numerous papers. In this survey, we distill key findings across numerous domains and provide researchers crucial access to important information by-(1) summarizing and comparing recent and classical graph robustness measures; (2) exploring which robustness measures are most applicable to different categories of networks (e.g., social, infrastructure); (3) reviewing common network attack strategies, and summarizing which attacks are most effective across different network topologies; and (4) extensive discussion on selecting defense techniques to mitigate attacks across a variety of networks. This survey guides researchers and practitioners in navigating the expansive field of network robustness, while summarizing answers to key questions. We conclude by highlighting current research directions and open problems.