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A matrix formalism is proposed for computations based on Picard--Lefschetz theory in a 2D case. The formalism is essentially equivalent to the computation of the intersection indices necessary for the Picard--Lefschetz formula and enables…

Mathematical Physics · Physics 2025-12-22 A. V. Shanin , A. I. Korolkov , N. M. Artemov , R. C. Assier

We view the reconstruction of CAD models in the boundary representation (B-Rep) as the detection of geometric primitives of different orders, i.e. vertices, edges and surface patches, and the correspondence of primitives, which are…

Computer Vision and Pattern Recognition · Computer Science 2022-05-31 Haoxiang Guo , Shilin Liu , Hao Pan , Yang Liu , Xin Tong , Baining Guo

Biomembranes play a central role in various phenomena like locomotion of cells, cell-cell interactions, packaging of nutrients, and in maintaining organelle morphology and functionality. During these processes, the membranes undergo…

Quantitative Methods · Quantitative Biology 2021-12-01 Debabrata Auddya , Xiaoxuan Zhang , Rahul Gulati , Ritvik Vasan , Krishna Garikipati , Padmini Rangamani , Shiva Rudraraju

Modern mesh generation pipelines whether learning-based or classical often produce outputs requiring post-processing to achieve production-quality geometry. This work introduces MeshCone, a convex optimization framework for guided mesh…

Graphics · Computer Science 2025-11-27 Alexander Valverde

We extend the construction of so-called encapsulated global summation-by-parts operators to the general case of a mesh which is not boundary conforming. Owing to this development, energy stable discretizations of nonlinear and variable…

Numerical Analysis · Mathematics 2023-05-30 Tomas Lundquist , Andrew Winters , Jan Nordström

In this work, we show that neural networks can be represented via the mathematical theory of quiver representations. More specifically, we prove that a neural network is a quiver representation with activation functions, a mathematical…

Machine Learning · Computer Science 2021-03-24 Marco Antonio Armenta , Pierre-Marc Jodoin

Structured point process data harvested from various platforms poses new challenges to the machine learning community. By imposing a matrix structure to repeatedly observed marked point processes, we propose a novel mixture model of…

Machine Learning · Statistics 2021-11-18 Lihao Yin , Ganggang Xu , Huiyan Sang , Yongtao Guan

Equations system constructors of hierarchical circuits play a central role in device modeling, nonlinear equations solving, and circuit design automation. However, existing constructors present limitations in applications to different…

Artificial Intelligence (AI) systems based solely on neural networks or symbolic computation present a representational complexity challenge. While minimal representations can produce behavioral outputs like locomotion or simple…

Neurons and Cognition · Quantitative Biology 2022-10-19 Bradly Alicea , Jesse Parent

Polygonal meshes provide an efficient representation for 3D shapes. They explicitly capture both shape surface and topology, and leverage non-uniformity to represent large flat regions as well as sharp, intricate features. This…

Machine Learning · Computer Science 2019-07-03 Rana Hanocka , Amir Hertz , Noa Fish , Raja Giryes , Shachar Fleishman , Daniel Cohen-Or

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insight by isolating the essential degrees of freedom that dictate the…

Statistical Mechanics · Physics 2023-04-12 Shriram Chennakesavalu , David J. Toomer , Grant M. Rotskoff

There have been recent efforts to learn more meaningful representations via fixed length codewords from mesh data, since a mesh serves as a complete model of underlying 3D shape compared to a point cloud. However, the mesh connectivity…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Eric Lei , Muhammad Asad Lodhi , Jiahao Pang , Junghyun Ahn , Dong Tian

Let f,g be two algebraically independent regular functions from the smooth affine complex variety U to the affine line. The associated exponential Gauss-Manin systems on the affine line are defined to be the cohomology sheaves of the direct…

Algebraic Geometry · Mathematics 2007-05-23 Marco Hien , Celine Roucairol

The paper explores the problem of \emph{spectral compressed sensing}, which aims to recover a spectrally sparse signal from a small random subset of its $n$ time domain samples. The signal of interest is assumed to be a superposition of $r$…

Information Theory · Computer Science 2015-01-05 Yuxin Chen , Yuejie Chi

We expand the toolbox of (co)homological methods in computational topology by applying the concept of persistence to sheaf cohomology. Since sheaves (of modules) combine topological information with algebraic information, they allow for…

Algebraic Topology · Mathematics 2022-04-29 Florian Russold

In this paper, we propose an efficient approach for the compression and representation of volumetric data utilizing coordinate-based networks and multi-resolution hash encoding. Efficient compression of volumetric data is crucial for…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Sudarshan Devkota , Sumanta Pattanaik

In complex materials, numerous intertwined phenomena underlie the overall response at macroscale. These phenomena can pertain to different engineering fields (mechanical , chemical, electrical), occur at different scales, can appear as…

Materials Science · Physics 2016-06-15 Pierre Jehel

A three-dimensional multi-scale computational homogenisation framework is developed for the prediction of nonlinear micro/meso-mechanical response of the fibre-reinforced polymer (FRP) composites. Two dominant damage mechanisms, i.e. matrix…

Computational Engineering, Finance, and Science · Computer Science 2016-10-18 Zahur Ullah , Lukasz Kaczmarczyk , Chris J. Pearce

A challenge in isogeometric analysis is constructing analysis-suitable volumetric meshes which can accurately represent the geometry of a given physical domain. In this paper, we propose a method to derive a spline-based representation of a…

Graphics · Computer Science 2017-03-22 Chiu Ling Chan , Cosmin Anitescu , Timon Rabczuk

We introduce the Stellar decomposition, a model for efficient topological data structures over a broad range of simplicial and cell complexes. A Stellar decomposition of a complex is a collection of regions indexing the complex's vertices…

Data Structures and Algorithms · Computer Science 2021-08-05 Riccardo Fellegara , Kenneth Weiss , Leila De Floriani