Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations

8 August 2021

Papers citing "Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations"

16 / 16 papers shown

Title
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Sean P. Cornelius 82 2 0 28 Jan 2025
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation Chuanqi Chen Nan Chen Yinling Zhang Jin-Long Wu AI4CE 36 2 0 26 Oct 2024
On the choice of the non-trainable internal weights in random feature maps Pinak Mandal Georg Gottwald Nicholas Cranch TPM 40 1 0 07 Aug 2024
Forecasting the Forced van der Pol Equation with Frequent Phase Shifts Using Reservoir Computing Sho Kuno Hiroshi Kori 18 0 0 23 Apr 2024
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation Chuanqi Chen Nan Chen Jin-Long Wu AI4CE 43 4 0 10 Apr 2024
Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series Akifumi Okuno Y. Morishita Yoh-ichi Mototake AI4TS 11 0 0 28 Jun 2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review Sibo Cheng César Quilodrán-Casas Said Ouala A. Farchi Che Liu ... Weiping Ding Yike Guo A. Carrassi Marc Bocquet Rossella Arcucci AI4CE 32 124 0 18 Mar 2023
Tensor-train methods for sequential state and parameter learning in state-space models Yiran Zhao Tiangang Cui 24 2 0 24 Jan 2023
Deep learning delay coordinate dynamics for chaotic attractors from partial observable data Charles D. Young M. Graham 11 16 0 20 Nov 2022
Catch-22s of reservoir computing Yuanzhao Zhang Sean P. Cornelius 21 10 0 18 Oct 2022
Asymptotic behavior of the forecast-assimilation process with unstable dynamics Dan Crisan M. Ghil 16 3 0 06 Feb 2022
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case R. Mojgani A. Chattopadhyay P. Hassanzadeh 24 15 0 01 Oct 2021
A Framework for Machine Learning of Model Error in Dynamical Systems Matthew E. Levine Andrew M. Stuart 27 67 0 14 Jul 2021
Forecasting Using Reservoir Computing: The Role of Generalized Synchronization Jason A. Platt Adrian S. Wong Randall Clark S. Penny H. Abarbanel AI4TS 20 4 0 04 Feb 2021
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems Alexander Wikner Jaideep Pathak Brian Hunt M. Girvan T. Arcomano I. Szunyogh Andrew Pomerance Edward Ott AI4CE 62 70 0 10 Feb 2020
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model D. Gagne H. Christensen A. Subramanian A. Monahan AI4CE BDL 41 139 0 10 Sep 2019