Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges

8 June 2023

Papers citing "Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges"

7 / 7 papers shown

Title
Fourier analysis of the physics of transfer learning for data-driven subgrid-scale models of ocean turbulence Moein Darman Pedram Hassanzadeh Laure Zanna Ashesh Chattopadhyay 35 0 0 21 Apr 2025
Global Estimation of Subsurface Eddy Kinetic Energy of Mesoscale Eddies Using a Multiple-input Residual Neural Network Chenyue Xie An-Kang Gao Xiyun Lu AI4Cl 102 0 0 14 Dec 2024
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling Shivam Barwey Riccardo Balin Bethany Lusch Saumil Patel Ramesh Balakrishnan Pinaki Pal R. Maulik V. Vishwanath GNN AI4CE 44 1 0 02 Oct 2024
On the importance of learning non-local dynamics for stable data-driven climate modeling: A 1D gravity wave-QBO testbed H. Pahlavan Pedram Hassanzadeh M. J. Alexander 49 1 0 07 Jul 2024
Interpretable structural model error discovery from sparse assimilation increments using spectral bias-reduced neural networks: A quasi-geostrophic turbulence test case R. Mojgani Ashesh Chattopadhyay Pedram Hassanzadeh 38 7 0 22 Sep 2023
Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl M. Cranmer 66 40 0 02 May 2023
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case R. Mojgani Ashesh Chattopadhyay Pedram Hassanzadeh 40 15 0 01 Oct 2021