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Less than 3% of people worldwide consider climate change not serious at all (Newman et al., 2021). It is typical for high school students to oversimplify complex problems (McComas, 1998), asking questions such as: “why don’t they just fix that?” when teaching common ES problems ...
2020, and the CompF4 Topical Group workshop [2] on April 7–8, 2022. These workshops drew attendees from all areas of High Energy Physics (HEP), with representatives from large and small experiments, computing
Open model developers have emerged as key actors in the political economy of artificial intelligence (AI), but we still have a limited understanding of collaborative practices in the open AI ecosystem. This paper responds to this gap with a three-part quantitative analysis of development activity o...
These metrics are mostly adapted from microscopy and molecular physics [100, 102]. The gradient surface model can increase the resemblance of the data to the natural world because it allows for the inclusion of more heterogeneity within each grid cell [101, 102]. Many surface metrics have ...
Since the global financial crisis of 2008–2009, many studies on financial systemic risk have been accumulated to date. One of the most distinctive features of this newly arising field is its interdisciplinary nature, with researchers having backgrounds in economics and finance, statistical physics, ...
Hybrid models: By combining physics-based models with ML techniques, solid solutions can be provided. Hybrid models can take advantage of physical knowledge while gaining knowledge from data-driven insights. Transfer learning: Transfer learning, which involves fine-tuning pre-trained models for particula...
Further considerations include the total size of the model, output structure and Just as no single ML architecture is the most appropriate for all problems, no single hardware architecture will be optimal for addressing every physics use-case effectively. As the technology and the field evolve, so...