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Any solid object can be decomposed into a collection of convex polytopes (in short, convexes). When a small number of convexes are used, such a decomposition can be thought of as a piece-wise approximation of the geometry. This…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Boyang Deng , Kyle Genova , Soroosh Yazdani , Sofien Bouaziz , Geoffrey Hinton , Andrea Tagliasacchi

Using Traizet's regeneration method, we prove the existence of many new 3-dimensional families of embedded, doubly periodic minimal surfaces. All these families have a foliation of 3-dimensional Euclidean space by vertical planes as a…

Differential Geometry · Mathematics 2010-01-15 Peter Connor , Matthias Weber

We present a continuous/discontinuous Galerkin method for approximating solutions to a fourth order elliptic PDE on a surface embedded in $\mathbb{R}^3$. A priori error estimates, taking both the approximation of the surface and the…

Numerical Analysis · Mathematics 2017-06-23 Karl Larsson , Mats G. Larson

Addressing the interpretability problem of NMF on Boolean data, Boolean Matrix Factorization (BMF) uses Boolean algebra to decompose the input into low-rank Boolean factor matrices. These matrices are highly interpretable and very useful in…

Machine Learning · Computer Science 2023-07-18 Sebastian Dalleiger , Jilles Vreeken

New approach to systems of polynomial recursions is developed based on the Carleman linearization procedure. The article is divided into two main sections: firstly, we focus on the case of uni-variable depth-one polynomial recurrences.…

Dynamical Systems · Mathematics 2021-12-16 Mikołaj Myszkowski

We prove the decomposition of arbitrary diagonal operators into tensor and matrix products of smaller matrices, focusing on the analytic structure of the resulting formulas and their inherent symmetries. Diagrammatic representations are…

Quantum Physics · Physics 2025-10-15 M. M. Fedin , A. A. Morozov

We construct an approximate trivializing map by using a Schwinger-Dyson equation. The advantage of this method is that: (1) The basis for the flow kernel can be chosen arbitrarily by hand. (2) It can be applied to the general action of…

High Energy Physics - Lattice · Physics 2022-12-23 Peter Boyle , Taku Izubuchi , Luchang Jin , Chulwoo Jung , Christoph Lehner , Nobuyuki Matsumoto , Akio Tomiya

We propose a new method to compute magnetic surfaces that are parametrized in Boozer coordinates for vacuum magnetic fields. We also propose a measure for quasi-symmetry on the computed surfaces and use it to design coils that generate a…

Plasma Physics · Physics 2022-08-17 Andrew Giuliani , Florian Wechsung , Matt Landreman , Georg Stadler , Antoine Cerfon

Interpolation of jointly infeasible predicates plays important roles in various program verification techniques such as invariant synthesis and CEGAR. Intrigued by the recent result by Dai et al.\ that combines real algebraic geometry and…

Logic in Computer Science · Computer Science 2017-09-04 Takamasa Okudono , Yuki Nishida , Kensuke Kojima , Kohei Suenaga , Kengo Kido , Ichiro Hasuo

Results of number of geometric operations (often used in technical practise, as e.g. the operation of blending) are in many cases surfaces described implicitly. Then it is a challenging task to recognize the type of the obtained surface,…

Symbolic Computation · Computer Science 2014-07-11 Jan Vršek , Miroslav Lávička

Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Xingyu Ren , Alexandros Lattas , Baris Gecer , Jiankang Deng , Chao Ma , Xiaokang Yang , Stefanos Zafeiriou

We consider the problem of approximate joint triangularization of a set of noisy jointly diagonalizable real matrices. Approximate joint triangularizers are commonly used in the estimation of the joint eigenstructure of a set of matrices,…

Numerical Analysis · Computer Science 2016-07-05 Nicolo Colombo , Nikos Vlassis

This paper describes and establishes the iteration-complexity of a doubly accelerated inexact proximal point (D-AIPP) method for solving the nonconvex composite minimization problem whose objective function is of the form $f+h$ where $f$ is…

Optimization and Control · Mathematics 2018-12-20 Jiaming Liang , Renato D. C. Monteiro

We propose a novel neural architecture for representing 3D surfaces, which harnesses two complementary shape representations: (i) an explicit representation via an atlas, i.e., embeddings of 2D domains into 3D; (ii) an implicit-function…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Omid Poursaeed , Matthew Fisher , Noam Aigerman , Vladimir G. Kim

A suitable measure for the similarity of shapes represented by parameterized curves or surfaces is the Fr\'echet distance. Whereas efficient algorithms are known for computing the Fr\'echet distance of polygonal curves, the same problem for…

Computational Geometry · Computer Science 2007-05-23 Helmut Alt , Maike Buchin

The biharmonic equation with Dirichlet and Neumann boundary conditions discretized using the mixed finite element method and piecewise linear (with the possible exception of boundary triangles) finite elements on triangular elements has…

Numerical Analysis · Mathematics 2022-04-21 Oded Stein , Eitan Grinspun , Alec Jacobson , Max Wardetzky

Given a tiling $\mathcal{T}$ of the plane by straight edge polygons, which is invariant by two independent translations, we construct a family of embedded triply periodic minimal surfaces which desingularizes $\mathcal{T}\times\mathbb{R}$.…

Differential Geometry · Mathematics 2010-03-15 Rami Younes

We survey incremental methods for minimizing a sum $\sum_{i=1}^mf_i(x)$ consisting of a large number of convex component functions $f_i$. Our methods consist of iterations applied to single components, and have proved very effective in…

Systems and Control · Computer Science 2017-12-21 Dimitri P. Bertsekas

Constrained low-rank matrix approximations have been known for decades as powerful linear dimensionality reduction techniques to be able to extract the information contained in large data sets in a relevant way. However, such low-rank…

Machine Learning · Computer Science 2021-12-20 Pierre De Handschutter , Nicolas Gillis , Xavier Siebert

Covering is an important type of data structure while covering-based rough sets provide an efficient and systematic theory to deal with covering data. In this paper, we use boolean matrices to represent and axiomatize three types of…

Artificial Intelligence · Computer Science 2013-03-05 Shiping Wang , Qingxin Zhu , William Zhu , Fan Min
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