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Existing convergence of distributed optimization methods in non-Euclidean geometries typically rely on kernel assumptions: (i) global Lipschitz smoothness and (ii) bi-convexity of the associated Bregman divergence function. Unfortunately,…

Optimization and Control · Mathematics 2026-03-16 Junwen Qiu , Ziyang Zeng , Leilei Mei , Junyu Zhang

We develop a formula for tautological integrals over geometric subsets of the Hilbert scheme of points on complex manifolds. As an illustration of the theory, we derive a new iterated residue formula for the number of nodal curves in…

Algebraic Geometry · Mathematics 2023-03-29 Gergely Bérczi

Many hypersurfaces in algebraic geometry, such as discriminants, arise as the projection of another variety. The real complement of such a hypersurface partitions its ambient space into open regions. In this paper, we propose a new method…

We present a novel hybrid strategy based on machine learning to improve curvature estimation in the level-set method. The proposed inference system couples enhanced neural networks with standard numerical schemes to compute curvature more…

Machine Learning · Computer Science 2022-09-29 Luis Ángel Larios-Cárdenas , Frédéric Gibou

Kernel methods for solving partial differential equations on surfaces have the advantage that those methods work intrinsically on the surface and yield high approximation rates if the solution to the partial differential equation is smooth…

Numerical Analysis · Mathematics 2024-10-04 Thomas Hangelbroek , Christian Rieger

In most classical approaches of computational geophysics for seismic wave propagation problems, complex surface topography is either accounted for by boundary-fitted unstructured meshes, or, where possible, by mapping the complex…

In this work we present an algorithm to construct an infinitely differentiable smooth surface from an input consisting of a (rectilinear) triangulation of a surface of arbitrary shape. The original surface can have non-trivial genus and…

Numerical Analysis · Mathematics 2019-10-01 Felipe Vico , Leslie Greengard , Michael O'Neil , Manas Rachh

In theory, diffusion curves promise complex color gradations for infinite-resolution vector graphics. In practice, existing realizations suffer from poor scaling, discretization artifacts, or insufficient support for rich boundary…

Numerical Analysis · Mathematics 2023-11-27 Seungbae Bang , Kirill Serkh , Oded Stein , Alec Jacobson

Boundary integral methods for the solution of boundary value PDEs are an alternative to `interior' methods, such as finite difference and finite element methods. They are attractive on domains with corners, particularly when the solution…

Numerical Analysis · Mathematics 2025-10-20 David De Wit

We propose implicit integrators for solving stiff differential equations on unit spheres. Our approach extends the standard backward Euler and Crank-Nicolson methods in Cartesian space by incorporating the geometric constraint inherent to…

Numerical Analysis · Mathematics 2025-03-25 Shingyu Leung

Multiscale mixed methods based on non-overlapping domain decompositions can efficiently handle the solution of significant subsurface flow problems in very heterogeneous formations of interest to the industry, especially when implemented on…

Numerical Analysis · Mathematics 2025-02-25 Dilong Zhou , Rafael Guiraldello , Felipe Pereira

We introduce a differentiable, end-to-end trainable framework for solving pixel-level grouping problems such as instance segmentation consisting of two novel components. First, we regress pixels into a hyper-spherical embedding space so…

Computer Vision and Pattern Recognition · Computer Science 2017-12-25 Shu Kong , Charless Fowlkes

A purely numerical approach to compact Riemann surfaces starting from plane algebraic curves is presented. The critical points of the algebraic curve are computed via a two-dimensional Newton iteration. The starting values for this…

Mathematical Physics · Physics 2015-11-02 J. Frauendiener , C. Klein

We present a novel method to perform numerical integration over curved polyhedra enclosed by high-order parametric surfaces. Such a polyhedron is first decomposed into a set of triangular and/or rectangular pyramids, whose certain faces…

Numerical Analysis · Mathematics 2022-05-11 Pablo Antolin , Xiaodong Wei , Annalisa Buffa

This paper presents an adaptive discretization strategy for level set topology optimization of structures based on hierarchical B-splines. This work focuses on the influence of the discretization approach and the adaptation strategy on the…

Numerical Analysis · Mathematics 2019-09-25 L. Noel , M. Schmidt , C. Messe , J. A. Evans , K. Maute

Localized features such as singularities, sharp gradients, discontinuities, and moving sources require adaptive finite element discretizations. Conventional refinement strategies introduce significant computational overhead through…

Computational Engineering, Finance, and Science · Computer Science 2026-04-29 Jan Niklas Schmäke , Martin Ruess

In this paper we describe an algorithm for implicitizing rational hypersurfaces in case there exists at most a finite number of base points. It is based on a technique exposed in math.AG/0210096, where implicit equations are obtained as…

Algebraic Geometry · Mathematics 2007-05-23 Laurent Buse , Marc Chardin

Recently, the theory of diffusion maps was extended to a large class of local kernels with exponential decay which were shown to represent various Riemannian geometries on a data set sampled from a manifold embedded in Euclidean space.…

Classical Analysis and ODEs · Mathematics 2015-09-28 Tyrus Berry , John Harlim

In numerical simulations of two-phase flows, the computation of the curvature of the interface is a crucial ingredient. Using a finite element and level set discretization, the discrete interface is typically the level set of a low order…

Numerical Analysis · Mathematics 2022-03-24 Dennis Zvegincev

Feature preprocessing continues to play a critical role when applying machine learning and statistical methods to tabular data. In this paper, we propose the use of the kernel density integral transformation as a feature preprocessing step.…

Machine Learning · Statistics 2023-10-20 Calvin McCarter
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