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The Super Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs.
If you use this software, please cite it using the metadata from this file.
tensorflow, climate-data, generative-adversarial-network, solar-energy, wind-energy, machine-learning, climate-change, deep-learning, renewable-energy
tensorflow, climate-data, generative-adversarial-network, solar-energy, wind-energy, machine-learning, climate-change, deep-learning, renewable-energy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |