Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model

6 January 2020

Papers citing "Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model"

32 / 32 papers shown

Title
Hybrid machine learning data assimilation for marine biogeochemistry Ieuan Higgs Ross Bannister Jozef Skákala Alberto Carrassi Stefano Ciavatta AI4Cl AI4CE 52 0 0 07 Apr 2025
Online model error correction with neural networks: application to the Integrated Forecasting System A. Farchi M. Chrust Marc Bocquet Massimo Bonavita 34 0 0 06 Mar 2024
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation Yi Xiao Lei Bai Wei Xue Kang Chen Tao Han Wanli Ouyang AI4Cl 44 24 0 16 Dec 2023
FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems Shiyuan Luo Juntong Ni Shengyu Chen Runlong Yu Yiqun Xie Licheng Liu Zhenong Jin Huaxiu Yao Xiaowei Jia 58 8 0 17 Nov 2023
Reconstruction, forecasting, and stability of chaotic dynamics from partial data Elise Özalp G. Margazoglou Luca Magri AI4TS 23 10 0 24 May 2023
Online machine-learning forecast uncertainty estimation for sequential data assimilation M. Sacco M. Pulido J. J. Ruiz P. Tandeo 35 3 0 12 May 2023
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates Ke Alexander Wang Matthew E. Levine Jiaxin Shi E. Fox 33 4 0 27 Apr 2023
Flipped Classroom: Effective Teaching for Time Series Forecasting P. Teutsch Patrick Mäder AI4TS 34 8 0 17 Oct 2022
A Transferable and Automatic Tuning of Deep Reinforcement Learning for Cost Effective Phishing Detection Orel Lavie A. Shabtai Gilad Katz AAML OffRL 37 1 0 19 Sep 2022
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models Sibo Cheng Jianhua Chen Charitos Anastasiou P. Angeli Omar K. Matar Yi-Ke Guo Christopher C. Pain Rossella Arcucci AI4CE 49 60 0 07 Apr 2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning Said Ouala Steven L. Brunton A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet PINN AI4TS AI4CE 45 10 0 11 Feb 2022
Classifying Turbulent Environments via Machine Learning M. Buzzicotti F. Bonaccorso 31 0 0 03 Jan 2022
Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation Austin Chennault Andrey A. Popov Amit N. Subrahmanya R. Cooper Ali Haisam Muhammad Rafid Anuj Karpatne Adrian Sandu 36 10 0 16 Nov 2021
Learning to Assimilate in Chaotic Dynamical Systems Michael McCabe Jed Brown AI4TS 41 10 0 01 Nov 2021
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 55 16 0 01 Oct 2021
Integrating Recurrent Neural Networks with Data Assimilation for Scalable Data-Driven State Estimation S. Penny T. A. Smith Tse-Chun Chen Jason A. Platt Hsin-Yi Lin M. Goodliff H. Abarbanel AI4CE 66 42 0 25 Sep 2021
Combining data assimilation and machine learning to estimate parameters of a convective-scale model Stefanie Legler T. Janjić 48 18 0 07 Sep 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations Georg Gottwald Sebastian Reich AI4CE 57 38 0 08 Aug 2021
State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics Quentin Malartic A. Farchi Marc Bocquet 41 19 0 23 Jul 2021
A comparison of combined data assimilation and machine learning methods for offline and online model error correction A. Farchi Marc Bocquet P. Laloyaux Massimo Bonavita Quentin Malartic OffRL 44 35 0 23 Jul 2021
Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation Truong-Vinh Hoang S. Krumscheid H. Matthies Raúl Tempone 31 7 0 15 Jun 2021
Bridging observation, theory and numerical simulation of the ocean using Machine Learning Maike Sonnewald Redouane Lguensat Daniel C. Jones P. Dueben J. Brajard Venkatramani Balaji AI4Cl AI4CE 51 100 0 26 Apr 2021
Latent Space Data Assimilation by using Deep Learning Mathis Peyron Anthony Fillion S. Gürol Victor Marchais Serge Gratton Pierre Boudier G. Goret AI4CE 31 44 0 01 Apr 2021
Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers Ashesh Chattopadhyay M. Mustafa Pedram Hassanzadeh Eviatar Bach K. Kashinath AI4CE 41 25 0 16 Mar 2021
Using machine learning to correct model error in data assimilation and forecast applications A. Farchi P. Laloyaux Massimo Bonavita Marc Bocquet AI4CE 36 103 0 23 Oct 2020
Combining data assimilation and machine learning to infer unresolved scale parametrisation J. Brajard A. Carrassi Marc Bocquet Laurent Bertino 28 113 0 09 Sep 2020
Supervised learning from noisy observations: Combining machine-learning techniques with data assimilation Georg Gottwald Sebastian Reich AI4CE 25 63 0 14 Jul 2020
Reconstruction of turbulent data with deep generative models for semantic inpainting from TURB-Rot database M. Buzzicotti F. Bonaccorso P. C. D. Leoni Luca Biferale AI4CE 35 51 0 16 Jun 2020
Online learning of both state and dynamics using ensemble Kalman filters Marc Bocquet A. Farchi Quentin Malartic 28 28 0 06 Jun 2020
Long-term prediction of chaotic systems with recurrent neural networks Huawei Fan Junjie Jiang Chun Zhang Xingang Wang Y. Lai 9 4 0 06 Mar 2020
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization Marc Bocquet J. Brajard A. Carrassi Laurent Bertino 21 104 0 17 Jan 2020
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 253 7,943 0 13 Jun 2015