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2002.05514
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Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems
Chaos (CHAOS), 2020
10 February 2020
Alexander Wikner
Jaideep Pathak
Brian Hunt
M. Girvan
T. Arcomano
I. Szunyogh
Andrew Pomerance
Edward Ott
AI4CE
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Papers citing
"Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems"
31 / 31 papers shown
Stochastic dynamics learning with state-space systems
Juan-Pablo Ortega
Florian Rossmannek
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Knowledge-based Neural Ordinary Differential Equations for Cosserat Rod-based Soft Robots
Tom Z. Jiahao
Ryan Adolf
Cynthia Sung
M. Ani Hsieh
300
1
0
14 Aug 2024
Development of an offline and online hybrid model for the Integrated Forecasting System
A. Farchi
M. Chrust
Marc Bocquet
Massimo Bonavita
275
0
0
06 Mar 2024
Gradient-free online learning of subgrid-scale dynamics with neural emulators
Hugo Frezat
Ronan Fablet
G. Balarac
Julien Le Sommer
551
6
0
30 Oct 2023
Leveraging Predictive Models for Adaptive Sampling of Spatiotemporal Fluid Processes
Sandeep Manjanna
Tom Z. Jiahao
M. A. Hsieh
164
0
0
03 Apr 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters
Inverse Problems (IP), 2023
Yuming Chen
D. Sanz-Alonso
Rebecca Willett
275
18
0
27 Jan 2023
Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization
Alexander Wikner
Joseph Harvey
M. Girvan
Brian R. Hunt
Andrew Pomerance
Thomas Antonsen
Edward Ott
319
7
0
09 Nov 2022
Online model error correction with neural networks in the incremental 4D-Var framework
Journal of Advances in Modeling Earth Systems (JAMES), 2022
A. Farchi
M. Chrust
Marc Bocquet
P. Laloyaux
Massimo Bonavita
336
36
0
25 Oct 2022
Catch-22s of reservoir computing
Physical Review Research (Phys. Rev. Res.), 2022
Yuanzhao Zhang
Sean P. Cornelius
370
19
0
18 Oct 2022
Online Dynamics Learning for Predictive Control with an Application to Aerial Robots
Conference on Robot Learning (CoRL), 2022
Tom Z. Jiahao
K. Y. Chee
M. A. Hsieh
328
32
0
19 Jul 2022
Learning Spatiotemporal Chaos Using Next-Generation Reservoir Computing
Chaos (Chaos), 2022
W. A. S. Barbosa
D. Gauthier
352
44
0
24 Mar 2022
Learning to Swarm with Knowledge-Based Neural Ordinary Differential Equations
IEEE International Conference on Robotics and Automation (ICRA), 2021
Tom Z. Jiahao
Lishuo Pan
M. A. Hsieh
350
12
0
10 Sep 2021
KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework for Aerial Robots
IEEE Robotics and Automation Letters (RA-L), 2021
K. Y. Chee
Tom Z. Jiahao
M. A. Hsieh
377
95
0
10 Sep 2021
Master memory function for delay-based reservoir computers with single-variable dynamics
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
F. Köster
S. Yanchuk
K. Lüdge
245
10
0
28 Aug 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations
Chaos (Chaos), 2021
Georg Gottwald
Sebastian Reich
AI4CE
275
46
0
08 Aug 2021
State, global and local parameter estimation using local ensemble Kalman filters: applications to online machine learning of chaotic dynamics
Quarterly Journal of the Royal Meteorological Society (QJRMS), 2021
Quentin Malartic
A. Farchi
Marc Bocquet
406
25
0
23 Jul 2021
A comparison of combined data assimilation and machine learning methods for offline and online model error correction
Journal of Computer Science (JCS), 2021
A. Farchi
Marc Bocquet
P. Laloyaux
Massimo Bonavita
Quentin Malartic
OffRL
345
51
0
23 Jul 2021
Model-free prediction of emergence of extreme events in a parametrically driven nonlinear dynamical system by Deep Learning
J. Meiyazhagan
S. Sudharsan
M. Senthilvelan
AI4TS
336
19
0
14 Jul 2021
A Framework for Machine Learning of Model Error in Dynamical Systems
Communications of the American Mathematical Society (Comm. Amer. Math. Soc.), 2021
Matthew E. Levine
Andrew M. Stuart
393
79
0
14 Jul 2021
Next Generation Reservoir Computing
Nature Communications (Nat Commun), 2021
D. Gauthier
Erik Bollt
Aaron Griffith
W. A. S. Barbosa
438
563
0
14 Jun 2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
GAMM-Mitteilungen (GAMM-Mitteilungen), 2021
Omer San
Adil Rasheed
T. Kvamsdal
249
68
0
26 Mar 2021
Robust Optimization and Validation of Echo State Networks for learning chaotic dynamics
Neural Networks (NN), 2021
A. Racca
Luca Magri
OOD
AAML
375
78
0
09 Feb 2021
Transfer learning of chaotic systems
Chaos (CHAOS), 2020
Yali Guo
Han Zhang
Liang Wang
Huawei Fan
Xingang Wang
AI4TS
216
22
0
15 Nov 2020
Using machine-learning modelling to understand macroscopic dynamics in a system of coupled maps
Francesco Borra
Marco Baldovin
AI4CE
161
2
0
08 Nov 2020
Using machine learning to correct model error in data assimilation and forecast applications
Quarterly Journal of the Royal Meteorological Society (QJRMS), 2020
A. Farchi
P. Laloyaux
Massimo Bonavita
Marc Bocquet
AI4CE
306
139
0
23 Oct 2020
Knowledge-Based Learning of Nonlinear Dynamics and Chaos
Tom Z. Jiahao
M. Hsieh
Eric Forgoston
427
36
0
07 Oct 2020
Kernel-based parameter estimation of dynamical systems with unknown observation functions
Chaos (CHAOS), 2020
Ofir Lindenbaum
A. Sagiv
Zhengchao Wan
Ronen Talmon
404
5
0
09 Sep 2020
OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle
Physical Review Fluids (Phys. Rev. Fluids), 2020
Haijun Yu
Xinyuan Tian
Weinan E
Qianxiao Li
AI4CE
346
56
0
06 Sep 2020
Effective models and predictability of chaotic multiscale systems via machine learning
Francesco Borra
A. Vulpiani
M. Cencini
174
13
0
02 Jul 2020
Combining Ensemble Kalman Filter and Reservoir Computing to predict spatio-temporal chaotic systems from imperfect observations and models
Futo Tomizawa
Y. Sawada
190
6
0
25 Jun 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
293
66
0
16 Jun 2020
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