Copertina

Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Chuanqi, Wang, Zhongrui, Chen, Nan, Wu, Jin-Long
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Lagrangian Conditional Gaussian Koopman Network for Data Assimilation and Prediction
di: Wang, Zhongrui, et al.
Pubblicazione: (2026)

CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation
di: Chen, Chuanqi, et al.
Pubblicazione: (2024)

CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation
di: Chen, Chuanqi, et al.
Pubblicazione: (2024)

CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting
di: Chen, Chuanqi, et al.
Pubblicazione: (2023)

Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator
di: Dong, Xinghao, et al.
Pubblicazione: (2024)

Neural Dynamical Operator: Continuous Spatial-Temporal Model with Gradient-Based and Derivative-Free Optimization Methods
di: Chen, Chuanqi, et al.
Pubblicazione: (2023)

Active Learning of Model Discrepancy with Bayesian Experimental Design
di: Yang, Huchen, et al.
Pubblicazione: (2025)

Data-Assimilated Model-Based Reinforcement Learning for Partially Observed Chaotic Flows
di: Ozan, Defne E., et al.
Pubblicazione: (2025)

Modelling Networked Dynamical System by Temporal Graph Neural ODE with Irregularly Partial Observed Time-series Data
di: Zou, Mengbang, et al.
Pubblicazione: (2024)

Koopman Identification of Nonlinear Systems via Reservoir Liftings
di: Gu, Weibin, et al.
Pubblicazione: (2026)

KODA: A Data-Driven Recursive Model for Time Series Forecasting and Data Assimilation using Koopman Operators
di: Singh, Ashutosh, et al.
Pubblicazione: (2024)

Efficient Spectral Control of Partially Observed Linear Dynamical Systems
di: Brahmbhatt, Anand, et al.
Pubblicazione: (2025)

LEVDA: Latent Ensemble Variational Data Assimilation via Differentiable Dynamics
di: Si, Phillip, et al.
Pubblicazione: (2026)

A Closed-Form Nonlinear Data Assimilation Algorithm for Multi-Layer Flow Fields
di: Wang, Zhongrui, et al.
Pubblicazione: (2024)

Koopman-based Deep Learning for Nonlinear System Estimation
di: Sun, Zexin, et al.
Pubblicazione: (2024)

RL-DAUNCE: Reinforcement Learning-Driven Data Assimilation with Uncertainty-Aware Constrained Ensembles
di: Behnoudfar, Pouria, et al.
Pubblicazione: (2025)

Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series
di: Okuno, Akifumi, et al.
Pubblicazione: (2023)

Online Bayesian Experimental Design for Partially Observed Dynamical Systems
di: Pérez-Vieites, Sara, et al.
Pubblicazione: (2025)

Stochastic and Non-local Closure Modeling for Nonlinear Dynamical Systems via Latent Score-based Generative Models
di: Dong, Xinghao, et al.
Pubblicazione: (2025)

Distributed Learning with Discretely Observed Functional Data
di: Liu, Jiading, et al.
Pubblicazione: (2024)

Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
di: Yang, Yiming, et al.
Pubblicazione: (2025)

Partially Observed Structural Causal Models
di: Orujlu, Turan, et al.
Pubblicazione: (2026)

Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
di: Naiman, Ilan, et al.
Pubblicazione: (2023)

On the Parameter Identifiability of Partially Observed Linear Causal Models
di: Dong, Xinshuai, et al.
Pubblicazione: (2024)

Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
di: Kim, Hojin, et al.
Pubblicazione: (2025)

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network
di: Rostamijavanani, Abdolvahhab, et al.
Pubblicazione: (2024)

Finite Sample Identification of Partially Observed Bilinear Dynamical Systems
di: Sattar, Yahya, et al.
Pubblicazione: (2025)

Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking
di: Chao, Chen-Hao, et al.
Pubblicazione: (2025)

The Ensemble Schr{ö}dinger Bridge filter for Nonlinear Data Assimilation
di: Sun, Hui
Pubblicazione: (2025)

Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments
di: Lillemark, Hansen Jin, et al.
Pubblicazione: (2026)

Data-Efficient Non-Gaussian Semi-Nonparametric Density Estimation for Nonlinear Dynamical Systems
di: Liao, Aaron R., et al.
Pubblicazione: (2026)

Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data
di: Wang, Yinsong, et al.
Pubblicazione: (2026)

Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
di: Mondal, Arnab Kumar, et al.
Pubblicazione: (2023)

Efficient Real-Time Adaptation of ROMs for Unsteady Flows Using Data Assimilation
di: Zighed, Ismaël, et al.
Pubblicazione: (2026)

Koopman Spectrum Nonlinear Regulators and Efficient Online Learning
di: Ohnishi, Motoya, et al.
Pubblicazione: (2021)

Jacobian-Enforced Neural Networks (JENN) for Improved Data Assimilation Consistency in Dynamical Models
di: Tian, Xiaoxu
Pubblicazione: (2024)

Partial Distribution Matching via Partial Wasserstein Adversarial Networks
di: Wang, Zi-Ming, et al.
Pubblicazione: (2024)

Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks
di: Qi, QingGuo, et al.
Pubblicazione: (2024)

SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series
di: Abushaqra, Futoon M., et al.
Pubblicazione: (2022)

Joint Registration and Conformal Prediction for Partially Observed Functional Data
di: Wang, Fangyi, et al.
Pubblicazione: (2025)