Tackling Climate Change with Machine Learning

最主要的官方网站：https://www.climatechange.ai

game theory：
[54] James Anderson, Fengyu Zhou, and Steven H Low. Disaggregation for networked power systems. In 2018 Power Systems Computation Conference (PSCC), pages 1–7. IEEE, 2018.
[55] Emre C Kara, Ciaran M Roberts, Michaelangelo Tabone, Lilliana Alvarez, Duncan S Callaway, and Emma M Stewart. Disaggregating solar generation from feeder-level measurements. Sustainable Energy, Grids and Networks, 13:112–121, 2018.
[56] Gregory S Ledva, Laura Balzano, and Johanna L Mathieu. Real-time energy disaggregation of a distribution feeder’s demand using online learning. IEEE Transactions on Power Systems, 33(5):4730–4740, 2018.
[57] Lynn H Kaack, Jay Apt, M Granger Morgan, and Patrick McSharry. Empirical prediction intervals improve energy forecasting. Proceedings of the National Academy of Sciences, 114(33):8752–8757, 2017.
[58] Priya Donti, Brandon Amos, and J Zico Kolter. Task-based end-to-end mod

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