Learning Stochastic Closures Using Ensemble Kalman Inversion

17 April 2020

Papers citing "Learning Stochastic Closures Using Ensemble Kalman Inversion"

11 / 11 papers shown

Title
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation Chuanqi Chen Nan Chen Yinling Zhang Jin-Long Wu AI4CE 59 2 0 26 Oct 2024
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator Xinghao Dong Chuanqi Chen Jin-Long Wu DiffM AI4CE 65 5 0 06 Aug 2024
Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods Oliver R. A. Dunbar Andrew B. Duncan Andrew M. Stuart Marie-Therese Wolfram 74 27 0 07 Apr 2021
Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM Oliver R. A. Dunbar A. Garbuno-Iñigo T. Schneider Andrew M. Stuart 49 59 0 24 Dec 2020
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization Marc Bocquet J. Brajard A. Carrassi Laurent Bertino 28 104 0 17 Jan 2020
Calibrate, Emulate, Sample Emmet Cleary A. Garbuno-Iñigo Shiwei Lan T. Schneider Andrew M. Stuart 57 103 0 10 Jan 2020
Sparse learning of stochastic dynamic equations L. Boninsegna Feliks Nuske C. Clementi 32 215 0 06 Dec 2017
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations T. Schneider Shiwei Lan Andrew M. Stuart J. Teixeira AI4Cl 50 315 0 31 Aug 2017
A new framework for extracting coarse-grained models from time series with multiscale structure S. Kalliadasis S. Krumscheid G. Pavliotis AI4TS 76 21 0 05 Sep 2014
Semi-Parametric Drift and Diffusion Estimation for Multiscale Diffusions S. Krumscheid G. Pavliotis S. Kalliadasis 95 31 0 08 Nov 2011
Maximum Likelihood Drift Estimation for Multiscale Diffusions A. Papavasiliou G. Pavliotis Andrew M. Stuart 150 65 0 19 Jun 2008