:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Ouyang, Du, Xiao, Jichang, Wang, Xiaoqun
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Numerical Analysis
Accesso online:	https://arxiv.org/abs/2407.14566
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Error analysis for empirical risk minimization over clipped ReLU networks in solving linear Kolmogorov partial differential equations
di: Xiao, Jichang, et al.
Pubblicazione: (2023)

Deep Learning Based on Randomized Quasi-Monte Carlo Method for Solving Linear Kolmogorov Partial Differential Equation
di: Xiao, Jichang, et al.
Pubblicazione: (2023)

Quasi-Monte Carlo for unbounded integrands with importance sampling
di: Ouyang, Du, et al.
Pubblicazione: (2023)

ALM-PINNs Algorithms for Solving Nonlinear PDEs and Parameter Inversion Problems
di: Tian, Yimeng, et al.
Pubblicazione: (2024)

Solving Nonlinear PDEs with Sparse Radial Basis Function Networks
di: Shao, Zihan, et al.
Pubblicazione: (2025)

Deep Picard Iteration for High-Dimensional Nonlinear PDEs
di: Han, Jiequn, et al.
Pubblicazione: (2024)

RBF-Generated Finite Difference Method Coupled with Quadratic Programming for Solving PDEs on Surfaces with Derivative Boundary Conditions
di: Chen, Peng, et al.
Pubblicazione: (2026)

Solving PDEs With Deep Neural Nets under General Boundary Conditions
di: Zhang, Chenggong
Pubblicazione: (2025)

Enhanced convergence rates of Adaptive Importance Sampling with recycling schemes via quasi-Monte Carlo methods
di: Chen, Jianlong, et al.
Pubblicazione: (2025)

Bean: A Language for Backward Error Analysis
di: Kellison, Ariel E., et al.
Pubblicazione: (2025)

Solving Roughly Forced Nonlinear PDEs via Misspecified Kernel Methods and Neural Networks
di: Baptista, Ricardo, et al.
Pubblicazione: (2025)

Nested Multilevel Monte Carlo with Preintegration for Efficient Risk Estimation
di: Xu, Yu, et al.
Pubblicazione: (2026)

Importance sampling and active subspace in quasi-Monte Carlo
di: Yu, Jiaxin, et al.
Pubblicazione: (2026)

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

Generalized Moving Least-Squares Methods for Solving Vector-valued PDEs on Unknown Manifolds
di: Li, Rongji, et al.
Pubblicazione: (2024)

Randomized Quasi-Monte Carlo and Importance Sampling for Super-Fast Growing Functions with Applications to Finance
di: Chen, Jianlong, et al.
Pubblicazione: (2025)

Optimal Error Estimates of a Linearized Backward Euler Localized Orthogonal Decomposition for the Landau-Lifshitz Equation
di: Ma, Zetao, et al.
Pubblicazione: (2026)

A New Adaptive Deep Learning based Reduced Order Model for Hybrid-Type Parabolic PDEs: Rigorous Error Analysis and Applications
di: Kotowski, Dawid, et al.
Pubblicazione: (2026)

Approximation Theory and Applications of Randomized Neural Networks for Solving High-Dimensional PDEs
di: De Ryck, T., et al.
Pubblicazione: (2025)

Deep Forward-Backward Dynamic Programming Schemes for High-Dimensional Semilinear Nonlocal PDEs and FBSDE with Jumps
di: Wang, Wansheng, et al.
Pubblicazione: (2025)

Latent Neural Operator Pretraining for Solving Time-Dependent PDEs
di: Wang, Tian, et al.
Pubblicazione: (2024)

Stochastic Quadrature Rules for Solving PDEs using Neural Networks
di: Taylor, Jamie M., et al.
Pubblicazione: (2025)

Solving High-Dimensional PDEs Using Linearized Neural Networks
di: Mao, Tong, et al.
Pubblicazione: (2026)

Incorporating Local Hölder Regularity into PINNs for Solving Elliptic PDEs
di: Zhou, Qirui, et al.
Pubblicazione: (2025)

Subspace Diffusion Posterior Sampling for Travel-Time Tomography
di: Cao, Xiang, et al.
Pubblicazione: (2024)

Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise
di: Hou, Yilong, et al.
Pubblicazione: (2024)

Solving PDEs on Unknown Manifolds with Machine Learning
di: Liang, Senwei, et al.
Pubblicazione: (2021)

A Quantum Spectral Framework for Solving PDEs
di: Huang, Chih-Kang, et al.
Pubblicazione: (2026)

Structured Backward Error for the WKB method
di: Corless, Robert M., et al.
Pubblicazione: (2024)

Numerical Reconstruction and Analysis of Backward Semilinear Subdiffusion Problems
di: Wu, Xu, et al.
Pubblicazione: (2025)

A Nonlinear Generalization of the Bauer-Fike Theorem and Novel Iterative Methods for Solving Nonlinear Eigenvalue Problems
di: Katende, Ronald
Pubblicazione: (2024)

A Meshfree RBF-FD Constant along Normal Method for Solving PDEs on Surfaces
di: Bayona, Víctor, et al.
Pubblicazione: (2024)

Neural Evolutionary Kernel Method: A Knowledge-Guided Framework for Solving Evolutionary PDEs
di: Ling, Shuo, et al.
Pubblicazione: (2026)

What Can One Expect When Solving PDEs Using Shallow Neural Networks?
di: He, Roy Y., et al.
Pubblicazione: (2025)

Spline-Based Stochastic Collocation Methods for Uncertainty Quantification in Nonlinear Hyperbolic PDEs
di: Chertock, Alina, et al.
Pubblicazione: (2024)

New High-Order Numerical Methods for Hyperbolic Systems of Nonlinear PDEs with Uncertainties
di: Chertock, Alina, et al.
Pubblicazione: (2023)

Finite Element Eigenfunction Network (FEENet): A Hybrid Framework for Solving PDEs on Complex Geometries
di: Li, Shiyuan, et al.
Pubblicazione: (2026)

TINNs: Time-Induced Neural Networks for Solving Time-Dependent PDEs
di: Dai, Chen-Yang, et al.
Pubblicazione: (2026)

Generalization Error Estimates of Machine Learning Methods for Solving High Dimensional Schrödinger Eigenvalue Problems
di: Yu, Hao, et al.
Pubblicazione: (2024)

A Mini-Batch Method for Solving Nonlinear PDEs with Gaussian Processes
di: Yang, Xianjin, et al.
Pubblicazione: (2023)