Bayesian inference of chaotic dynamics by merging data assimilation,
machine learning and expectation-maximization

Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization

17 January 2020

Laurent Bertino

Papers citing "Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization"

14 / 14 papers shown

Title
Online model error correction with neural networks: application to the Integrated Forecasting System A. Farchi M. Chrust Marc Bocquet Massimo Bonavita 26 0 0 06 Mar 2024
Learning 4DVAR inversion directly from observations Arthur Filoche J. Brajard A. Charantonis Dominique Béréziat 29 2 0 17 Nov 2022
Ensemble forecasts in reproducing kernel Hilbert space family Benjamin Dufée Berenger Hug É. Mémin G. Tissot 24 1 0 29 Jul 2022
STEADY: Simultaneous State Estimation and Dynamics Learning from Indirect Observations Jiayi Wei Jarrett Holtz Işıl Dillig Joydeep Biswas 37 4 0 02 Mar 2022
A Systematic Exploration of Reservoir Computing for Forecasting Complex Spatiotemporal Dynamics Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 43 33 0 21 Jan 2022
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 22 42 0 25 Sep 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations Georg Gottwald Sebastian Reich AI4CE 46 37 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 39 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 31 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 26 7 0 15 Jun 2021
Using machine learning to correct model error in data assimilation and forecast applications A. Farchi P. Laloyaux Massimo Bonavita Marc Bocquet AI4CE 28 101 0 23 Oct 2020
Combining data assimilation and machine learning to infer unresolved scale parametrisation J. Brajard A. Carrassi Marc Bocquet Laurent Bertino 12 112 0 09 Sep 2020
Learning Variational Data Assimilation Models and Solvers Ronan Fablet Bertrand Chapron Lucas Drumetz É. Mémin O. Pannekoucke F. Rousseau 19 67 0 25 Jul 2020
Online learning of both state and dynamics using ensemble Kalman filters Marc Bocquet A. Farchi Quentin Malartic 12 27 0 06 Jun 2020