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pro vyhledávání: '"Stott, Jacklynn"'
Autor:
Price, Ilan, Sanchez-Gonzalez, Alvaro, Alet, Ferran, Andersson, Tom R., El-Kadi, Andrew, Masters, Dominic, Ewalds, Timo, Stott, Jacklynn, Mohamed, Shakir, Battaglia, Peter, Lam, Remi, Willson, Matthew
Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather, to planning renewable energy use. Here, we introduce GenCast, a
Externí odkaz:
http://arxiv.org/abs/2312.15796
Autor:
Lam, Remi, Sanchez-Gonzalez, Alvaro, Willson, Matthew, Wirnsberger, Peter, Fortunato, Meire, Alet, Ferran, Ravuri, Suman, Ewalds, Timo, Eaton-Rosen, Zach, Hu, Weihua, Merose, Alexander, Hoyer, Stephan, Holland, George, Vinyals, Oriol, Stott, Jacklynn, Pritzel, Alexander, Mohamed, Shakir, Battaglia, Peter
Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute resources to improve forecast accuracy, but cannot directly use historical
Externí odkaz:
http://arxiv.org/abs/2212.12794
Autor:
Addanki, Ravichandra, Battaglia, Peter W., Budden, David, Deac, Andreea, Godwin, Jonathan, Keck, Thomas, Li, Wai Lok Sibon, Sanchez-Gonzalez, Alvaro, Stott, Jacklynn, Thakoor, Shantanu, Veličković, Petar
Effectively and efficiently deploying graph neural networks (GNNs) at scale remains one of the most challenging aspects of graph representation learning. Many powerful solutions have only ever been validated on comparatively small datasets, often wit
Externí odkaz:
http://arxiv.org/abs/2107.09422
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