Cover Image

Unbiased and Second-Order-Free Training for High-Dimensional PDEs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Seo, Jaemin, Lee, Surin, Lee, Jae Yong
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Numerical Analysis Optimization and Control 65C30, 68TO7
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data-Free Asymptotics-Informed Operator Networks for Singularly Perturbed PDEs
by: Lee, Jinsil, et al.
Published: (2025)

SVD-Preconditioned Gradient Descent Method for Solving Nonlinear Least Squares Problems
by: Chang, Zhipeng, et al.
Published: (2026)

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications
by: Lee, Youngkyu, et al.
Published: (2024)

Objective Value Change and Shape-Based Accelerated Optimization for the Neural Network Approximation
by: Xie, Pengcheng, et al.
Published: (2025)

Discontinuous Galerkin finite element operator network for solving non-smooth PDEs
by: Chawla, Kapil, et al.
Published: (2026)

A practical randomized trust-region method to escape saddle points in high dimension
by: Dragomir, Radu-Alexandru, et al.
Published: (2026)

Learning nonnegative matrix factorizations from compressed data
by: Chaudhry, Abraar, et al.
Published: (2024)

Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies
by: Kopaničáková, Alena, et al.
Published: (2023)

Residual Multi-Fidelity Neural Network Computing
by: Davis, Owen, et al.
Published: (2023)

Finite Element Operator Network for Solving Elliptic-type parametric PDEs
by: Lee, Jae Yong, et al.
Published: (2023)

Generative Modelling of Lévy Area for High Order SDE Simulation
by: Jelinčič, Andraž, et al.
Published: (2023)

Losing momentum in continuous-time stochastic optimisation
by: Jin, Kexin, et al.
Published: (2022)

Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes
by: Chen, Yifan, et al.
Published: (2023)

A Layer Separation Optimization Framework for Cross-Entropy Training in Deep Learning
by: Liu, Yaru, et al.
Published: (2026)

Power Homotopy for Zeroth-Order Non-Convex Optimizations
by: Xu, Chen
Published: (2025)

On the fast convergence of minibatch heavy ball momentum
by: Bollapragada, Raghu, et al.
Published: (2022)

Leveraging Operator Learning to Accelerate Convergence of the Preconditioned Conjugate Gradient Method
by: Kopaničáková, Alena, et al.
Published: (2025)

Resolving gradient pathology in physics-informed epidemiological models
by: Golooba, Nickson, et al.
Published: (2026)

Deep Neural ODE Operator Networks for PDEs
by: Li, Ziqian, et al.
Published: (2025)

Generalized convergence of the deep BSDE method: a step towards fully-coupled FBSDEs and applications in stochastic control
by: Negyesi, Balint, et al.
Published: (2024)

On the Shape of the Symmetric Solution Set of a Linear Complementarity Problem with Interval Data
by: Schäfer, Uwe
Published: (2025)

A Unified Framework for Lifted Training and Inversion Approaches
by: Wang, Xiaoyu, et al.
Published: (2025)

Improved Convergence Factor of Windowed Anderson Acceleration for Symmetric Fixed-Point Iterations
by: Garner, Casey, et al.
Published: (2023)

Approximation of Solution Operators for High-dimensional PDEs
by: Gaby, Nathan, et al.
Published: (2024)

Bi-level iterative regularization for inverse problems in nonlinear PDEs
by: Nguyen, Tram Thi Ngoc
Published: (2023)

A Deep Learning algorithm to accelerate Algebraic Multigrid methods in Finite Element solvers of 3D elliptic PDEs
by: Caldana, Matteo, et al.
Published: (2023)

Optimization over the intersection of manifolds
by: Yang, Yan, et al.
Published: (2026)

Deep Hilbert--Galerkin Methods for Infinite-Dimensional PDEs and Optimal Control
by: Cohen, Samuel N., et al.
Published: (2026)

Learning to Control: The iUzawa-Net for Nonsmooth Optimal Control of Linear PDEs
by: Song, Yongcun, et al.
Published: (2026)

Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees
by: Lu, Zhaosong, et al.
Published: (2024)

An Additively Preconditioned Trust Region Strategy for Machine Learning
by: Alegría, Samuel Cruz, et al.
Published: (2025)

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators
by: Fabiani, Gianluca, et al.
Published: (2025)

Global Optimization with A Power-Transformed Objective and Gaussian Smoothing
by: Xu, Chen
Published: (2024)

Policy Gradient with Second Order Momentum
by: Sun, Tianyu
Published: (2025)

Unbiased Gradients for a Class of Conditional Stochastic Optimization Problems
by: Alvarez, Miguel, et al.
Published: (2026)

Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients
by: Chada, Neil K., et al.
Published: (2023)

Low-rank optimization on Tucker tensor varieties
by: Gao, Bin, et al.
Published: (2023)

Optimization on product manifolds under a preconditioned metric
by: Gao, Bin, et al.
Published: (2023)

DyKAF: Dynamical Kronecker Approximation of the Fisher Information Matrix for Gradient Preconditioning
by: Yudin, Nikolay, et al.
Published: (2025)

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