Symbolic regression (SR) seeks explicit equations that explain observed data, and recent methods increasingly employ large language models (LLMs) and agents for equation discovery. However, these systems typically rely on manually designed workflows and prompts. We argue that the SR agent harness should itself be an op...
Qian Li, Yu-Xiao Hu, Qi-Hao Duan et al.· 0 citations
Ultra-short-term forecasting of densely distributed photovoltaic (PV) systems remains challenging because external meteorological and satellite products may not adequately resolve rapid local variations, while heterogeneous PV systems exhibit different generation responses under similar atmospheric conditions. Meanwhil...
Da-Yin Chen, Xiao-Dan Shi, Xin Xu et al.· 0 citations
DeepX‐GAN (Dependence‐Enhanced Embedding for Physical eXtremes—Generative Adversarial Network) is introduced, a deep generative model that explicitly captures the spatial structure of rare extremes and enables the simulation of statistically plausible extremes beyond the observed record, evaluated against long climate...
Xin-Yue Liu, Xiao Peng, Shu-Yue Yan et al.· Earth's Future· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.