:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Yao, Jiaqi, Mitchell, Lewis, Maclean, John, Saratchandran, Hemanth
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Dynamical Systems Computational Physics
Acceso en línea:	https://arxiv.org/abs/2509.14219
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

Probabilistic Forecasting for Dynamical Systems with Missing or Imperfect Data
por: Rout, Siddharth, et al.
Publicado: (2025)

Subspace-Distance-Enabled Active Learning for Efficient Data-Driven Model Reduction of Parametric Dynamical Systems
por: Kapadia, Harshit, et al.
Publicado: (2025)

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

LES-SINDy: Laplace-Enhanced Sparse Identification of Nonlinear Dynamical Systems
por: Zheng, Haoyang, et al.
Publicado: (2024)

Invariant Measures in Time-Delay Coordinates for Unique Dynamical System Identification
por: Botvinick-Greenhouse, Jonah, et al.
Publicado: (2024)

On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations
por: Rajkumar, Santosh Mohan, et al.
Publicado: (2026)

A Score Filter Enhanced Data Assimilation Framework for Data-Driven Dynamical Systems
por: Tang, Jingqiao, et al.
Publicado: (2026)

Fast and Flexible Probabilistic Forecasting of Dynamical Systems using Flow Matching and Physical Perturbation
por: Rout, Siddharth, et al.
Publicado: (2025)

Physics-Informed Boundary Integral Networks (PIBI-Nets): A Data-Driven Approach for Solving Partial Differential Equations
por: Nagy-Huber, Monika, et al.
Publicado: (2023)

Learning About Structural Errors in Models of Complex Dynamical Systems
por: Wu, Jin-Long, et al.
Publicado: (2023)

Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems
por: Koike, Tomoki, et al.
Publicado: (2026)

Consistent Projection of Langevin Dynamics: Preserving Thermodynamics and Kinetics in Coarse-Grained Models
por: Nateghi, Vahid, et al.
Publicado: (2025)

Dynamic Basis Function Interpolation for Adaptive In Situ Data Integration in Ocean Modeling
por: DeSantis, Derek, et al.
Publicado: (2023)

Learning Macroscopic Dynamics from Partial Microscopic Observations
por: Chen, Mengyi, et al.
Publicado: (2024)

Invariant Measures for Data-Driven Dynamical System Identification: Analysis and Application
por: Botvinick-Greenhouse, Jonah
Publicado: (2025)

VeMo: A Lightweight Data-Driven Approach to Model Vehicle Dynamics
por: Oddo, Girolamo, et al.
Publicado: (2025)

Deep Recurrent Stochastic Configuration Networks for Modelling Nonlinear Dynamic Systems
por: Dang, Gang, et al.
Publicado: (2024)

Automated Global Analysis of Experimental Dynamics through Low-Dimensional Linear Embeddings
por: Moore, Samuel A., et al.
Publicado: (2024)

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics
por: Suriyanarayanan, Ashwin, et al.
Publicado: (2026)

Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
por: Brenner, Manuel, et al.
Publicado: (2022)

Synergizing Transport-Based Generative Models and Latent Geometry for Stochastic Closure Modeling
por: Dong, Xinghao, et al.
Publicado: (2026)

Weighted Birkhoff Averages Accelerate Data-Driven Methods
por: Bou-Sakr-El-Tayar, Maria, et al.
Publicado: (2025)

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

Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge
por: Schmidt, Oliver T., et al.
Publicado: (2026)

Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging
por: Zakariaei, Niloufar, et al.
Publicado: (2024)

PINN-Obs: Physics-Informed Neural Network-Based Observer for Nonlinear Dynamical Systems
por: Farkane, Ayoub, et al.
Publicado: (2025)

Iterative Learning Control of Fast, Nonlinear, Oscillatory Dynamics (Preprint)
por: Brooks, John W., et al.
Publicado: (2024)

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics
por: Yin, Junqi, et al.
Publicado: (2024)

On Convex Data-Driven Inverse Optimal Control for Nonlinear, Non-stationary and Stochastic Systems
por: Garrabe, Emiland, et al.
Publicado: (2023)

ADAM-SINDy: An Efficient Optimization Framework for Parameterized Nonlinear Dynamical System Identification
por: Viknesh, Siva, et al.
Publicado: (2024)

Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing
por: Norton, Declan A., et al.
Publicado: (2025)

Sparse identification of quasipotentials via a combined data-driven method
por: Lin, Bo, et al.
Publicado: (2024)

Higher order quantum reservoir computing for non-intrusive reduced-order models
por: Jain, Vinamr, et al.
Publicado: (2024)

Optimized Dynamic Mode Decomposition for Reconstruction and Forecasting of Atmospheric Chemistry Data
por: Velegar, Meghana, et al.
Publicado: (2024)

Preconditioned Attention: Enhancing Efficiency in Transformers
por: Saratchandran, Hemanth
Publicado: (2026)

Sparse Identification of Nonlinear Dynamics with Conformal Prediction
por: Fasel, Urban
Publicado: (2025)

Deep Learning for Koopman Operator Estimation in Idealized Atmospheric Dynamics
por: Millard, David, et al.
Publicado: (2024)

Hierarchy of extreme-event predictability in turbulence revealed by machine learning
por: Yang, Yuxuan, et al.
Publicado: (2026)

Extracting Signal out of Chaos: Advancements on MAGI for Bayesian Analysis of Dynamical Systems
por: Wu, Skyler
Publicado: (2024)