1 citations · 2 across the 4 of their papers we have counts for
4 papers
An intercomparison of generative machine learning methods for downscaling precipitation at fine spatial scales
Neelesh Rampal, Bryn Ward-Leikis, Yun Sing Koh +7
Machine learning (ML) offers a computationally efficient approach for generating large ensembles of high-resolution climate projections, but deterministic ML methods often smooth f…
XAI4Extremes: An interpretable machine learning framework for understanding extreme-weather precursors under climate change
Jiawen Wei, Aniruddha Bora, Vivek Oommen +7
Extreme weather events are increasing in frequency and intensity due to climate change. This, in turn, is exacting a significant toll in communities worldwide. While prediction ski…
CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints
Xin Wang, Jianda Chen, Juntao Yang +8
Accurate and efficient climate simulations are crucial for understanding Earth's evolving climate. However, current general circulation models (GCMs) face challenges in capturing u…
Data-driven Surface Solar Irradiance Estimation using Neural Operators at Global Scale
Alberto Carpentieri, Jussi Leinonen, Jeff Adie +3
Accurate surface solar irradiance (SSI) forecasting is essential for optimizing renewable energy systems, particularly in the context of long-term energy planning on a global scale…