67 citations · 170 across the 6 of their papers we have counts for
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cs.LG2024★ 3 cited
Towards Physically Consistent Deep Learning For Climate Model Parameterizations
Birgit Kühbacher, Fernando Iglesias-Suarez, Niki Kilbertus +1
Climate models play a critical role in understanding and projecting climate change. Due to their complexity, their horizontal resolution of about 40-100 km remains too coarse to re…
cs.LG2023★ 19 cited
ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
Sungduk Yu, Zeyuan Hu, Akshay Subramaniam +44
Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderst…