The data synergy effects of time-series deep learning models in hydrology

6 January 2021

Papers citing "The data synergy effects of time-series deep learning models in hydrology"

5 / 5 papers shown

Title
Surveying Attitudinal Alignment Between Large Language Models Vs. Humans Towards 17 Sustainable Development Goals Qingyang Wu Ying Xu Tingsong Xiao Yunze Xiao Yitong Li ... Yichi Zhang Shanghai Zhong Yuwei Zhang Wei Lu Yifan Yang 78 2 0 17 Jan 2025
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 20 10 0 08 Oct 2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences Chaopeng Shen A. Appling Pierre Gentine Toshiyuki Bandai H. Gupta ... Chris Rackauckas Tirthankar Roy Chonggang Xu Binayak Mohanty K. Lawson AI4CE 34 14 0 10 Jan 2023
Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy D. Feng Jiangtao Liu K. Lawson Chaopeng Shen BDL AI4CE 10 117 0 28 Mar 2022
Continental-scale streamflow modeling of basins with reservoirs: towards a coherent deep-learning-based strategy Wenyu Ouyang K. Lawson D. Feng L. Ye Chi Zhang Chaopeng Shen AI4TS AI4CE 54 60 0 12 Jan 2021