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From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling

30 July 2020

Papers citing "From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling"

21 / 21 papers shown

Title
Scientifically-Interpretable Reasoning Network (ScIReN): Uncovering the Black-Box of Nature Joshua Fan Haodi Xu Feng Tao Md Nasim Marc Grimson Yiqi Luo Carla P. Gomes 21 0 0 16 Jun 2025
Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations Abdolmehdi Behroozi Chaopeng Shen and Daniel Kifer AI4CE 120 0 0 13 May 2025
Deep Learning Meets Process-Based Models: A Hybrid Approach to Agricultural Challenges Yue Shi Liangxiu Han Xin Zhang Tam Sobeih T. Gaiser Nguyen Huu Thuy Dominik Behrend A. Srivastava Krishnagopal Halder F. Ewert AI4CE 62 0 0 22 Apr 2025
Foundation Models for Environmental Science: A Survey of Emerging Frontiers Runlong Yu Shengyu Chen Yiqun Xie Huaxiu Yao J. Willard X. Jia AI4CE 129 1 0 05 Apr 2025
A Deep State Space Model for Rainfall-Runoff Simulations Yihan Wang Lujun Zhang Annan Yu N. Benjamin Erichson Tiantian Yang 114 1 0 28 Jan 2025
Knowledge-guided Machine Learning: Current Trends and Future Prospects Anuj Karpatne X. Jia Vipin Kumar 103 12 0 24 Mar 2024
Towards Interpretable Physical-Conceptual Catchment-Scale Hydrological Modeling using the Mass-Conserving-Perceptron Yuan-Heng Wang Hoshin V. Gupta AI4CE 150 3 0 25 Jan 2024
Enhancing Low-Order Discontinuous Galerkin Methods with Neural Ordinary Differential Equations for Compressible Navier--Stokes Equations Shinhoo Kang Emil M. Constantinescu AI4CE 106 0 0 29 Oct 2023
A Mass-Conserving-Perceptron for Machine Learning-Based Modeling of Geoscientific Systems Yuan-Heng Wang Hoshin V. Gupta AI4CE 94 6 0 12 Oct 2023
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 141 10 0 08 Oct 2023
Learning Regionalization using Accurate Spatial Cost Gradients within a Differentiable High-Resolution Hydrological Model: Application to the French Mediterranean Region Ngo Nghi Truyen Huynh P. Garambois Franccois Colleoni B. Renard H. Roux J. Demargne M. Jay-Allemand P. Javelle 51 7 0 02 Aug 2023
Probing the limit of hydrologic predictability with the Transformer network Jiangtao Liu Yuchen Bian Chaopeng Shen AI4TS 44 10 0 21 Jun 2023
Perspectives on AI Architectures and Co-design for Earth System Predictability M. Mudunuru James A. Ang M. Halappanavar Simon D. Hammond Maya Gokhale ... Tushar Krishna S. Sreepathi Matthew R. Norman Ivy Bo Peng Philip W. Jones 36 1 0 07 Apr 2023
Fully Convolutional Networks for Dense Water Flow Intensity Prediction in Swedish Catchment Areas Aleksis Pirinen Olof Mogren Mårten Västerdal 64 0 0 04 Apr 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 110 15 0 10 Jan 2023
Fast Calibration for Computer Models with Massive Physical Observations Shurui Lv Yan Wang Junrong Yu 49 1 0 23 Nov 2022
Differentiable Programming for Earth System Modeling Maximilian Gelbrecht Alistair J R White S. Bathiany Niklas Boers 89 19 0 29 Aug 2022
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 72 121 0 28 Mar 2022
Bathymetry Inversion using a Deep-Learning-Based Surrogate for Shallow Water Equations Solvers Xiaofeng Liu Yalan Song Chaopeng Shen AI4CE 89 10 0 05 Mar 2022
Surrogate Model for Shallow Water Equations Solvers with Deep Learning Yalan Song Chaopeng Shen Xiaofeng Liu AI4CE 52 5 0 20 Dec 2021
The data synergy effects of time-series deep learning models in hydrology K. Fang Daniel Kifer K. Lawson D. Feng Chaopeng Shen AI4CE 127 81 0 06 Jan 2021