#error analysis
14 papers match
Error Analysis of Neural-Network-Based Engression
Juntong Chen, Zijian Guo, Xinwei Shen
The paper analyzes the theoretical error of neural‑network‑based engression, a method for learning conditional distributions via an energy score, and derives convergence rates by d…
How Benchmarks Mis-Score Computer-Use Agents
Zihan Dong, Zhiyuan Ma, Zekun Wang +5
The paper examines how current benchmarks for computer-use agents often give inaccurate scores due to issues in task design, trajectory observation, scoring, and reporting, and pro…
Optimal control problems for quasi-linear parabolic equations and their linear approximations
Xu Liu, Meisai Wang, Xu Zhang
The paper studies optimal control problems for quasi‑linear parabolic PDEs and shows that, for sufficiently small initial data and targets, the optimal controls and trajectories ca…
Optimal Error Estimates of a Finite Element Method for Semilinear SPDEs with Additive Noise and Nonsmooth Initial Data
Jitendra Nath Naik, Lok Pati Tripathi
The paper analyzes strong error bounds for finite element spatial discretizations combined with a linearly implicit Euler time scheme applied to semilinear parabolic SPDEs with add…
On the optimality of dimension truncation error rates for a class of parametric partial differential equations
Philipp A. Guth, Vesa Kaarnioja
The paper analyzes the error introduced when infinite-dimensional random field inputs in parametric PDEs are truncated to finite dimensions, and proves that the known dimension‑tru…
Structure-preserving Lagrange-multiplier methods for mean curvature flow and their error bounds
Balázs Kovács, Buyang Li, Christian Lubich
The paper introduces and analyzes structure‑preserving finite element methods that use Lagrange multipliers to enforce energy‑decreasing behavior in numerical simulations of mean c…
Error Analysis of a Fully-Discrete Implicit -Scheme with WG-FEM for Parabolic Singularly Perturbed Boundary Turning Point Problems
Aayushman Raina, Srinivasan Natesan
The paper presents a weak Galerkin finite element method combined with an implicit θ‑time discretization on a Shishkin mesh for solving parabolic singularly perturbed boundary turn…
Discontinuous in time Virtual Element method for Darcy equations coupled with Multi Species Transport with First Order Reaction Network
Ruben Caraballo, Franco Dassi
The paper presents a numerical scheme that combines the Virtual Element Method for spatial discretization with a discontinuous Galerkin time integrator to solve Darcy flow coupled…
Continuous Cross Approximation of Matrices Arising Out of Kernel Functions
Sumit Singh, Sivaram Ambikasaran
The paper introduces a residual‑energy based continuous method for constructing low‑rank approximations of kernel matrices by adaptively selecting optimal nodes, providing converge…
Error Analysis of Triangular Optimal Transport Maps for Filtering
Mohammad Al-Jarrah, Bamdad Hosseini, Niyizhen Jin +2
The paper analyzes estimation errors of optimal‑transport‑based filtering algorithms, extending Brenier map error results to conditional Brenier maps and demonstrating the approach…
A Weighted Integral-Regularized Finite Difference Scheme for the Tempered Fractional Laplacian
Mingyi Wang, Lisen Ding, Dongling Wang
The paper proposes a weighted integral‑regularized finite difference scheme for the tempered fractional Laplacian, providing high‑order error bounds and efficient solution via FFT‑…
Convolution quadrature based on a truncated trapezoidal rule
Matteo Ferrari
The paper introduces a family of A‑stable second‑order multistep methods called the truncated trapezoidal rule, derives optimal coefficients to minimize the error constant, and sho…
A Reynolds-semi-robust H(div)-conforming method for unsteady incompressible power-law flows
Lourenço Beirão da Veiga, Daniele A. Di Pietro, Kirubell B. Haile
The paper develops and analyzes an H(div)-conforming discontinuous Galerkin method with upwind stabilization for unsteady incompressible power‑law (non‑Newtonian) flows, providing…
Inf-Sup Neural Networks for High Dimensional PDEs
Ziren Chen, Hailiang Liu
The paper introduces a neural‑network framework that rewrites high‑dimensional partial differential equations as inf‑sup (saddle‑point) optimization problems using a Lagrange multi…
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