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Neural Closure Models for Dynamical Systems
v1v2v3 (latest)

Neural Closure Models for Dynamical Systems

Proceedings of the Royal Society A (Proc. R. Soc. A), 2020
27 December 2020
Abhinav Gupta
Pierre FJ Lermusiaux
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Neural Closure Models for Dynamical Systems"

17 / 17 papers shown
Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulence
Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulence
Anantha N.S. Babu
Akhil Sadam
Pierre F.J. Lermusiaux
DiffM
201
2
0
01 Jul 2025
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural OperatorJournal of Computational Physics (JCP), 2024
Xinghao Dong
Chuanqi Chen
Jin-Long Wu
DiffMAI4CE
431
16
0
06 Aug 2024
Hybrid$^2$ Neural ODE Causal Modeling and an Application to Glycemic
  Response
Hybrid2^22 Neural ODE Causal Modeling and an Application to Glycemic Response
Bob Junyi Zou
Matthew E. Levine
D. Zaharieva
Ramesh Johari
Emily Fox
430
8
0
27 Feb 2024
Evaluation of Deep Neural Operator Models toward Ocean Forecasting
Evaluation of Deep Neural Operator Models toward Ocean ForecastingOceans (OCEANS), 2023
Ellery Rajagopal
Anantha N.S. Babu
Tony Ryu
P. Haley
C. Mirabito
Pierre FJ Lermusiaux
AI4ClAI4CE
232
4
0
22 Aug 2023
A Multifidelity deep operator network approach to closure for multiscale
  systems
A Multifidelity deep operator network approach to closure for multiscale systemsComputer Methods in Applied Mechanics and Engineering (CMAME), 2023
Shady E. Ahmed
P. Stinis
AI4CE
260
21
0
15 Mar 2023
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical
  Musculoskeletal System Based on Non-intrusive Model Order Reduction
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order ReductionArchive of applied mechanics (1991) (Arch. Appl. Mech.), 2023
Jonas Kneifl
D. Rosin
Oliver Röhrle
Jörg Fehr
AI4CE
247
19
0
13 Feb 2023
Generalized Neural Closure Models with Interpretability
Generalized Neural Closure Models with InterpretabilityScientific Reports (Sci Rep), 2023
Abhinava Gupta
Pierre FJ Lermusiaux
AI4CE
264
16
0
15 Jan 2023
Stable rank-adaptive Dynamically Orthogonal Runge-Kutta schemes
Stable rank-adaptive Dynamically Orthogonal Runge-Kutta schemesSIAM Journal on Scientific Computing (SISC), 2022
A. Charous
Pierre FJ Lermusiaux
188
8
0
15 Nov 2022
Bayesian Learning of Coupled Biogeochemical-Physical Models
Bayesian Learning of Coupled Biogeochemical-Physical Models
Abhinav Gupta
Pierre FJ Lermusiaux
324
8
0
12 Nov 2022
Comparison of neural closure models for discretised PDEs
Comparison of neural closure models for discretised PDEsComputers and Mathematics with Applications (CMA), 2022
Hugo Melchers
D. Crommelin
B. Koren
Vlado Menkovski
B. Sanderse
182
26
0
26 Oct 2022
Variational multiscale reinforcement learning for discovering reduced
  order closure models of nonlinear spatiotemporal transport systems
Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systemsScientific Reports (Sci Rep), 2022
Omer San
Suraj Pawar
Adil Rasheed
AI4CE
162
8
0
07 Jul 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and
  Vibroacoustic
A Review of Machine Learning Methods Applied to Structural Dynamics and VibroacousticMechanical systems and signal processing (MSSP), 2022
Barbara Z Cunha
C. Droz
A. Zine
Stéphane Foulard
M. Ichchou
AI4CE
264
134
0
13 Apr 2022
Bounded nonlinear forecasts of partially observed geophysical systems
  with physics-constrained deep learning
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
PINNAI4TSAI4CE
441
13
0
11 Feb 2022
Output-weighted and relative entropy loss functions for deep learning
  precursors of extreme events
Output-weighted and relative entropy loss functions for deep learning precursors of extreme events
S. Rudy
T. Sapsis
324
22
0
01 Dec 2021
Learning Stable Deep Dynamics Models for Partially Observed or Delayed
  Dynamical Systems
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems
Andreas Schlaginhaufen
Philippe Wenk
Andreas Krause
Florian Dorfler
238
22
0
27 Oct 2021
Super-resolution data assimilation
Super-resolution data assimilation
Sébastien Barthélémy
J. Brajard
Laurent Bertino
F. Counillon
AI4Cl
181
39
0
04 Sep 2021
A Framework for Machine Learning of Model Error in Dynamical Systems
A Framework for Machine Learning of Model Error in Dynamical SystemsCommunications of the American Mathematical Society (Comm. Amer. Math. Soc.), 2021
Matthew E. Levine
Andrew M. Stuart
382
79
0
14 Jul 2021
1
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