:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Qin, Chenxin, Liu, Ruhao, Li, Maocai, Li, Shengyuan, Liu, Yi, Zhou, Chichun
Format:	Preprint
Published:	2021
Subjects:	Machine Learning Numerical Analysis
Online Access:	https://arxiv.org/abs/2105.11309
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations
by: Aghaei, Alireza Afzal
Published: (2024)

Deep Domain Decomposition Method for Solving the Variational Inequality Problems
by: Wang, Yiyang, et al.
Published: (2026)

Deep Ritz Physics-Informed Neural Network Method for Solving the Variational Inequality
by: Zhou, Qijia, et al.
Published: (2026)

Approximation properties of neural ODEs
by: De Marinis, Arturo, et al.
Published: (2025)

Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks
by: Zhang, Borong, et al.
Published: (2022)

Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models
by: Zhang, Borong, et al.
Published: (2024)

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

Efficient Tensor Completion Algorithms for Highly Oscillatory Operators
by: Singh, Navjot, et al.
Published: (2025)

Overparameterization of deep ResNet: zero loss and mean-field analysis
by: Ding, Zhiyan, et al.
Published: (2021)

Supervised and Unsupervised Neural Network Solver for First Order Hyperbolic Nonlinear PDEs
by: Baba, Zakaria, et al.
Published: (2026)

DeepONet for Solving Nonlinear Partial Differential Equations with Physics-Informed Training
by: Yang, Yahong
Published: (2024)

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

A Fourth-Order Cut-cell Multigrid Method for Solving Elliptic Equations on Arbitrary Domains
by: Liu, Jiyu, et al.
Published: (2026)

ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations
by: Tang, Shanshan, et al.
Published: (2019)

A Gaussian Process Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations
by: Mora, Carlos, et al.
Published: (2024)

Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
by: Krach, Florian, et al.
Published: (2022)

A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models
by: Li, Gen, et al.
Published: (2024)

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

A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations
by: Liu, Shu, et al.
Published: (2024)

Sampling via Stochastic Interpolants by Langevin-based Velocity and Initialization Estimation in Flow ODEs
by: Duan, Chenguang, et al.
Published: (2026)

Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework
by: Andersson, William, et al.
Published: (2023)

Finite Expression Method for Solving High-Dimensional Partial Differential Equations
by: Liang, Senwei, et al.
Published: (2022)

NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia
by: Pal, Avik, et al.
Published: (2024)

A Stiff Order Condition Theory for Runge-Kutta Methods Applied to Semilinear ODEs
by: Roberts, Steven B., et al.
Published: (2025)

DeltaPhi: Physical States Residual Learning for Neural Operators in Data-Limited PDE Solving
by: Yue, Xihang, et al.
Published: (2024)

Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method
by: Hardwick, Gareth, et al.
Published: (2024)

Nonlocality and Nonlinearity Implies Universality in Operator Learning
by: Lanthaler, Samuel, et al.
Published: (2023)

DeepContour: A Hybrid Deep Learning Framework for Accelerating Generalized Eigenvalue Problem Solving via Efficient Contour Design
by: Chen, Yeqiu, et al.
Published: (2025)

A Relaxed Step-Ratio Constraint for Time-Fractional Cahn--Hilliard Equations: Analysis and Computation
by: Li, Shipeng, et al.
Published: (2025)

Higher Order Approximation Rates for ReLU CNNs in Korobov Spaces
by: Li, Yuwen, et al.
Published: (2025)

Adaptive-Growth Randomized Neural Networks for Level-Set Computation of Multivalued Nonlinear First-Order PDEs with Hyperbolic Characteristics
by: Dang, Haoning, et al.
Published: (2026)

Faster Diffusion Models via Higher-Order Approximation
by: Li, Gen, et al.
Published: (2025)

A Probabilistic Framework for Solving High-Frequency Helmholtz Equations via Diffusion Models
by: Zou, Yicheng, et al.
Published: (2026)

Nonparametric Filtering, Estimation and Classification using Neural Jump ODEs
by: Heiss, Jakob, et al.
Published: (2024)

Approximation of Some Nonlinear Fractional Order BVPs by Weighted Residual Methods
by: Ruman, Umme, et al.
Published: (2024)

Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations
by: Zhou, Wei, et al.
Published: (2024)

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

Newton Informed Neural Operator for Computing Multiple Solutions of Nonlinear Partials Differential Equations
by: Hao, Wenrui, et al.
Published: (2024)

FBSJNN: A Theoretically Interpretable and Efficiently Deep Learning method for Solving Partial Integro-Differential Equations
by: Ye, Zaijun, et al.
Published: (2024)

An Efficient Exponential Sum Approximation of Power-Law Kernels for Solving Fractional Differential Equation
by: Chaudhary, Renu, et al.
Published: (2025)