Applied Math · Mathematics & Statistics
Numerical Analysis
The newest papers in Numerical Analysis that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
285 papers, from 31 August 2026 to 5 November 2026: 212 arXiv preprints and 73 OpenAlex records.
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Newest papers, page 5
Low Residuals, Wrong Value: Learning the Viscosity Solution of Hamilton-Jacobi-Isaacs Equations with PINNs
Physics-informed neural networks (PINNs) and other residual-trained solvers judge a candidate solution by the size of its sampled PDE residual.LowNet: Looped Wavelet Neural Networks with 24 Learnable Parameters for Solving Poisson Equations
Poisson equations frequently appear in various fields, such as mathematics, physics and informatics.Integrable building blocks for symplectic neural networks: learned-type layers, fiber-preserving layers, and what a single layer can do
Exactly symplectic neural networks are built almost exclusively from shear maps and gain expressivity only through depth.Spatial Discretization Error for Quantum Chemistry Simulation
Nonrelativistic quantum chemistry is based on the Schrödinger equation in continuous, unbounded space.Transformers as Adaptive Kernel Learners across Tasks for In-Context Learning
Transformers have emerged as a dominant architecture in modern machine learning, with in-context learning (ICL) enabling models to adapt to new tasks by conditioning on prompts, without any…Cayley access models for matrix functions: reachable class and cost
We study how to compute $f(A)b$ on a quantum computer, where $A$ is Hermitian.Reusable QUBO-Derived Block-Schur Inverse Factors for Fixed-Operator Finite-Difference PDE Solvers
Many simulations of partial differential equations require the repeated solution of linear systems whose matrix remains fixed while the righthand side changes.Certified neural approximations for parabolic obstacle problems
Residual-trained neural surrogates carry no error guarantee, a limitation for free-boundary problems such as phase change and contact.Near optimal gap in the Lonely Runner Conjecture
For a set $V$ of $n$ distinct positive integers, let $\mathrm{ML}(V)=\max_{t\in\mathbb{R}/\mathbb{Z}}\min_{v\in V}\|vt\|$, where $\|x\|$ is the distance from $x$ to the nearest integer.Adaptive Randomized Neural Networks for PDEs: Structure-Aware Feature Redistribution and Residual-Driven Block Enrichment
Randomized neural networks retain an output-linear least-squares solve, but globally sampled random features may fail to capture the spatial and scale structure of PDE solutions.Change the Number, Change the Answer: Assessing Rating Scale Sensitivity in LLM-Based Text Scoring
Large language models (LLMs) are increasingly used in computational social science to assign scalar scores to social and psychological constructs.Optimal approximation of smooth functions by ReLU neural networks
We study uniform approximation of the Hölder ball $\mathcal H_1^s([0,1]^D)$ by fully connected ReLU networks.On the Complexity of Linear Programs with Parametric Constraint Matrices
While sensitivity analysis for linear programs with parametric right- hand side vectors is well established, cases involving parametric constraint matrices remain less explored.Orientation Estimation of Cryo-EM Images for Molecules with Arbitrary Symmetry by Semidefinite Programming
This paper extends the non-unique games framework introduced in Bandeira et al. (2020) to address symmetric structures.Graph Coarsening Enables Escaping Local Optima in Compute-Constrained Nonconvex MAX-CUT
Because its binary optimization landscape contains exponentially many local optima, MAX-CUT is highly sensitive to initialization.CLNO: Conservative Local Neural Operator for Compressible Flow Prediction
We propose a conservative local neural operator (CLNO) for accurate and generalizable autoregressive prediction of compressible flows.Neural Network Preconditioning: A Case Study for the Solution of the Parametric Helmholtz Equation
This work presents a hybrid numerical approach for solving linear systems arising from the discretization of the two-dimensional parametric Helmholtz equation.A Method for Exact Enforcement of Boundary Conditions on General Curved Triangular Domains: Algorithm and Application to Scientific Machine Learning
We present a method for enforcing exactly Dirichlet, Neumann, and Robin conditions on general triangular domains with arbitrarily curved boundaries.Noise-Induced Restoration of Entropy Concavity Near Gaussian Equilibrium
We study a quantitative form of noise-induced restoration of entropy concavity for one-dimensional nonequilibrium states relaxing toward a Gaussian thermal equilibrium.A Counterexample to Three Conjectures of Luo
We give a single counterexample to Conjectures 1--3 as stated in Luo's paper: a minimal two-tetrahedron triangulation of the lens space L(3,1) with a null-homotopic loop edge.