:: Library Catalog

Imaxe de Portada

Gardado en:

Detalles Bibliográficos
Autor Principal:	Stinis, Panagiotis
Formato:	Preprint
Publicado:	2003
Subjects:	Numerical Analysis
Acceso en liña:	https://arxiv.org/abs/math/0307133
Tags:	Engadir etiqueta Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!

Títulos similares

Parametric Reduced Order Models for the Generalized Kuramoto--Sivashinsky Equations
por: Mizan, Md Rezwan Bin, et al.
Publicado: (2025)

Holistic finite differences accurately model the dynamics of the Kuramoto-Sivashinsky equation
por: MacKenzie, T., et al.
Publicado: (2000)

Regularity and error estimates in physics-informed neural networks for the Kuramoto-Sivashinsky equation
por: Rahman, Mohammad Mahabubur, et al.
Publicado: (2025)

Time-Dependent Solutions to the 2D Kuramoto-Sivashinsky Equation via Pseudospectral Method on a Rectangular Domain
por: Žigić, Jovan
Publicado: (2023)

Rigorous Numerics for Partial Differential Equations: the Kuramoto-Sivashinsky equation
por: Zgliczynski, P., et al.
Publicado: (2000)

Fully discrete finite element methods for the stochastic Kuramoto-Sivashinsky equation with multiplicative noise
por: Nguyen, Hung D., et al.
Publicado: (2025)

Stochastic Optimal Prediction with Application to Averaged Euler Equations
por: Bell, John, et al.
Publicado: (2000)

Symbolic dynamics for the Kuramoto-Sivashinsky PDE on the line II
por: Wilczak, Daniel, et al.
Publicado: (2024)

Concurrent multi-parameter learning demonstrated on the Kuramoto-Sivashinsky equation
por: Pachev, Benjamin, et al.
Publicado: (2021)

A multifidelity approach to continual learning for physical systems
por: Howard, Amanda, et al.
Publicado: (2023)

Improving the accuracy of physics-informed neural networks via last-layer retraining
por: Qadeer, Saad, et al.
Publicado: (2026)

Efficient Transformer-Inspired Variants of Physics-Informed Deep Operator Networks
por: Wei, Zhi-Feng, et al.
Publicado: (2025)

SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks
por: Jacob, Bruno, et al.
Publicado: (2024)

Multifidelity Kolmogorov-Arnold Networks
por: Howard, Amanda A., et al.
Publicado: (2024)

A Neural Network for the Identical Kuramoto Equation: Architectural Considerations and Performance Evaluation
por: Panigrahi, Nishantak, et al.
Publicado: (2025)

Stochastic Parareal Algorithm for Stochastic Differential Equations
por: Wang, Huanxin, et al.
Publicado: (2025)

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications
por: Williams, Emily, et al.
Publicado: (2024)

From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
por: Wan, Ruyin, et al.
Publicado: (2025)

Stabilizing PDE--ML coupled systems
por: Qadeer, Saad, et al.
Publicado: (2025)

Splitting Method for Stochastic Navier-Stokes Equations
por: Zhu, Jie, et al.
Publicado: (2025)

Encoded Forward Backward Stochastic Neural Network for High-Dimensional Backward Stochastic Differential Equations and Parabolic Partial Differential Equations
por: Zhang, Zhao, et al.
Publicado: (2026)

E-PINNs: Epistemic Physics-Informed Neural Networks
por: Jacob, Bruno, et al.
Publicado: (2025)

Kuramoto model on Sierpinski Gasket I: Harmonic maps
por: Medvedev, Georgi S., et al.
Publicado: (2024)

Adaptive Boundary Control of the Kuramoto-Sivashinsky Equation Under Intermittent Sensing
por: Belhadjoudja, Mohamed Camil, et al.
Publicado: (2024)

SOC-MartNet: A Martingale Neural Network for the Hamilton-Jacobi-Bellman Equation without Explicit inf H in Stochastic Optimal Controls
por: Cai, Wei, et al.
Publicado: (2024)

Geometry-preserving Numerical Scheme for Riemannian Stochastic Differential Equations
por: Wang, Xi, et al.
Publicado: (2025)

Generalized Finite Difference Method for Solving Stochastic Diffusion Equations
por: Mojarrad, Faezeh Nassajian
Publicado: (2024)

Tangent Space Parametrization for Stochastic Differential Equations on SO(n)
por: Wang, Xi, et al.
Publicado: (2025)

A Stochastic Method for Solving Time-Fractional Differential Equations
por: Guidotti, Nicolas L., et al.
Publicado: (2023)

Strong Approximation of Stochastic Semiclassical Schroedinger Equation with Multiplicative Noise
por: Ji, Lihai, et al.
Publicado: (2024)

Parareal Algorithms for Stochastic Maxwell Equations Driven by Multiplicative Noise
por: Zhang, Liying, et al.
Publicado: (2025)

A Reduced Basis Method for the Stochastic Landau-Lifshitz-Gilbert Equation
por: Scaglioni, Andrea, et al.
Publicado: (2025)

Explicit $θ$-Schemes for Solving Anticipated Backward Stochastic Differential Equations
por: Hu, Mingshang, et al.
Publicado: (2019)

Strong Stability Preservation for Stochastic Partial Differential Equations
por: Woodfield, James
Publicado: (2024)

Stochastic Parameter Prediction in Cardiovascular Problems
por: Bakhshaei, Kabir, et al.
Publicado: (2024)

Modified Equations for Stochastic Optimization
por: Perko, Stefan
Publicado: (2025)

A High-order Backpropagation Algorithm for Neural Stochastic Differential Equation Model
por: Sheng, Daili, et al.
Publicado: (2025)

Geometric Milstein Scheme for Stochastic Differential Equations on SO(n) and SE(n)
por: Wang, Xi, et al.
Publicado: (2026)

Adaptive Mesh Construction for the Numerical Solution of Stochastic Differential Equations with Markovian Switching
por: Kelly, Cónall, et al.
Publicado: (2024)

Application of Kalman Filter in Stochastic Differential Equations
por: Bao, Wencheng, et al.
Publicado: (2024)