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 2
Representation-Aware Closed-Surface Parameterization: Exact Sensitivity Analysis and Pole-Aware Planar Preconditioning
Surface parameterization is a fundamental task in geometry processing and shape analysis.Unbiased Low-Rank Approximation for Repeated Matrix-Vector Multiplication: Stability and Optimal Sampling
Replacing the matrix in an iteration with random low-rank matrices can reduce the cost of matrix-vector multiplication.Closed-Form Gaussian Mixture Representations of d-Dimensional Triangulated Domains
We derive a Gaussian Mixture (GM) representation of a full-dimensional subset of Euclidean space with finite volume from a finite simplicial triangulation in closed form.Minimum-Norm Interpolation in Weighted Variation Spaces: Direct and Inverse Problems
We study minimum-norm interpolation in weighted variation spaces generated by ReLU$^s$ ridge functions on the unit ball, where $s$ is a positive integer.Online Autotuning of Algebraic Multigrid via Contextual Bandits and Reinforcement Learning
Algebraic multigrid (AMG) methods are widely used for solving large sparse linear systems, but their efficiency depends strongly on interacting setup and solve parameters.Accelerating posterior sampling in Bayesian inverse problems with diffusion models: an online-offline perspective
Bayesian inverse problems require both informative prior models and computationally feasible posterior inference.Convergence of non-symmetric forms with changing reference measures
We develop a functional-analytic theory of convergence for non-symmetric generalized Dirichlet forms defined on a sequence of Hilbert spaces $H_n$ converging to a limit space $H$ in the sense of…General Frequency Principle for Linear Approximation Classes
In this paper, we study a general frequency principle under gradient descent training for the finite linear approximation classes.Feature-preserving interface reconstruction using piecewise circles and cusps
We present a geometric interface reconstruction method for Volume-of-Fluid (VOF) simulations that captures both curved interfaces and sharp features using only volume fraction data.Extending Sample-based Quantum Diagonalization to Systems of Linear Equations
Solving systems of linear equations, $Ax=b$, is a ubiquitous task in computational science.High-fidelity simulation and reduced-order modeling of optical pumping in quantum devices
Spatially resolved modeling of optically pumped alkali-metal vapors requires the solution of a high-dimensional nonlinear diffusive quantum master equation (DQME) coupled to state-dependent light…Functional Tensor Trains for High-Order Greeks and Exposure Tails of Multi-Asset Structured Products
Risk management of worst-of autocallables needs price sensitivities (Greeks) up to third order and the potential future exposure, a tail quantile of the note's future value.The Rise of Low Precision Floating Point
Floating point computing has dominated scientific computations since the 1950s because of its versatile ability to approximate real numbers with both sufficiently high precision and sufficiently…Learning to evolve by matching velocities
Learning the continuous-time evolution of nonlinear dynamical systems relies on trajectory-based objectives, which require simulating the learned dynamics during training and backpropagating through…Fast rigid rotational alignment of voxelized 3-D density maps in sliced Wasserstein distance
We develop a fast method for the rigid alignment of voxelized three-dimensional density functions over $\mathsf{SO}(3)$ using sliced optimal transport.Data-driven Random-feature Approximation of Koopman Generators of Nonlinear Continuous-time Systems
Learning continuous-time dynamical systems from data is an active area of research.Integer-Quantized Hierarchical Matrices with Adaptive Bit Allocation
We present an adaptive bitwidth allocation method for quantizing low-rank factors in hierarchical matrices in order to decrease storage while meeting a given constraint on their reconstruction error.NEOPIC: A Neural Operator Framework for Particle-based Kinetic Plasma Simulations
We introduce NEOPIC, a framework for learning the field operator in particle-based methods applied to kinetic plasma simulations.Immersed Boundary Electrodiffusion in the Wasserstein Gradient Flow Formalism: Global Well-Posedness, Non-Equilibrium Thermodynamics, and Singular Asymptotics
We introduce a unified optimal transport framework for the Immersed Boundary (IB) electrodiffusion active pump model.Kernel-based Interpolatory Methods for Context Compression of Attention Mechanisms
The bottleneck of attention mechanisms, which are the fundamental building block of modern language models, is their quadratic complexity in terms of context size.