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In this paper, we study how to find rational motions that move a line along a given rational ruled surface. Our goal is to find motions with the lowest possible degree using dual quaternions. While similar problems for point trajectories…

Rings and Algebras · Mathematics 2025-09-01 Zülal Derin Yaqub , Hans-Peter Schröcker

Neural implicit representations, which encode a surface as the level set of a neural network applied to spatial coordinates, have proven to be remarkably effective for optimizing, compressing, and generating 3D geometry. Although these…

Computer Vision and Pattern Recognition · Computer Science 2022-06-27 Nicholas Sharp , Alec Jacobson

Design of robots at the small scale is a trial-and-error based process, which is costly and time-consuming. There are no good dynamic simulation tools to predict the motion or performance of a microrobot as it moves against a substrate. At…

Robotics · Computer Science 2019-07-31 Jiayin Xie , Chenghao Bi , David J. Cappelleri , Nilanjan Chakraborty

Graph Neural Networks (GNNs) are a powerful representational tool for solving problems on graph-structured inputs. In almost all cases so far, however, they have been applied to directly recovering a final solution from raw inputs, without…

Machine Learning · Statistics 2020-01-16 Petar Veličković , Rex Ying , Matilde Padovano , Raia Hadsell , Charles Blundell

We give an accessible introduction and elaboration on the methods used in obtaining a geodesic, which is the curve of shortest length connecting two points lying on the surface of a function. This is found through computing what's known as…

Functional Analysis · Mathematics 2020-10-21 Andrew R. Tawfeek

Neural surfaces (e.g., neural map encoding, deep implicits and neural radiance fields) have recently gained popularity because of their generic structure (e.g., multi-layer perceptron) and easy integration with modern learning-based setups.…

Graphics · Computer Science 2025-03-18 Romy Williamson , Niloy J. Mitra

Connections between integration along hypersufaces, Radon transforms, and neural networks are exploited to highlight an integral geometric mathematical interpretation of neural networks. By analyzing the properties of neural networks as…

Machine Learning · Statistics 2019-07-05 Soheil Kolouri , Xuwang Yin , Gustavo K. Rohde

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

Using data from a simulated cup drawing process, we demonstrate how the inherent geometrical structure of cup meshes can be used to effectively prune an artificial neural network in a straightforward way.

Machine Learning · Computer Science 2021-09-14 Raoul Heese , Lukas Morand , Dirk Helm , Michael Bortz

Real-time generation of natural-looking floor plans is vital in games with dynamic environments. This paper presents an algorithm to generate suburban house floor plans in real-time. The algorithm is based on the work presented in [1].…

Graphics · Computer Science 2012-11-27 Maysam Mirahmadi , Abdallah Shami

In this paper, the dynamics of heuristic algorithms for constructing small vertex covers (or independent sets) of finite-connectivity random graphs is analysed. In every algorithmic step, a vertex is chosen with respect to its vertex…

Statistical Mechanics · Physics 2015-06-24 Martin Weigt

We study the problem of finding neck-like features on a surface. Applications for such cuts include robotics, mesh segmentation, and algorithmic applications. We provide a new definition for a surface bottleneck -- informally, it is the…

Computational Geometry · Computer Science 2026-01-14 Sam Ruggerio , Sariel Har-Peled

We introduce Geometric Neural Operators (GNPs) for accounting for geometric contributions in data-driven deep learning of operators. We show how GNPs can be used (i) to estimate geometric properties, such as the metric and curvatures, (ii)…

Machine Learning · Computer Science 2024-04-18 Blaine Quackenbush , Paul J. Atzberger

In this paper we propose a heuristic technique for distributing points on the surface of a unit n-dimensional Euclidean sphere, generated as the orbit of a finite cyclic subgroup of orthogonal matrices, the so called cyclic group codes.…

Information Theory · Computer Science 2015-09-21 João E. Strapasson , Cristiano Torezzan

NURBS curve is widely used in Computer Aided Design and Computer Aided Geometric Design. When a single weight approaches infinity, the limit of a NURBS curve tends to the corresponding control point. In this paper, a kind of control…

Graphics · Computer Science 2017-06-27 Yue Zhang , Chun-Gang Zhu

We describe a method for modeling the geometry of porous materials. The approach enables the independent selection of crucial parameters, including porosity, pore size distribution, pore shape, and connectivity. Consequently, it can…

Materials Science · Physics 2024-04-19 Felix Buchele , Patric Müller , Michael Blank , Thorsten Pöschel

These lecture notes focus on some numerical linear algebra algorithms in scientific computing. We assume that students are familiar with elementary linear algebra concepts such as vector spaces, systems of equations, matrices, norms,…

History and Overview · Mathematics 2024-12-31 Davoud Mirzaei

This paper presents a method to obtain geometric registrations between high-genus ($g\geq 1$) surfaces. Surface registration between simple surfaces, such as simply-connected open surfaces, has been well studied. However, very few works…

Computational Geometry · Computer Science 2014-03-27 Chengfeng Wen , Lok Ming Lui

The problem of polycube construction or deformation is an essential problem in computer graphics. In this paper, we present a robust, simple, efficient and automatic algorithm to deform the meshes of arbitrary shapes into their polycube…

Graphics · Computer Science 2018-07-24 Hui Zhao , Na Lei , Xuan Li , Peng Zeng , Ke Xu , Xianfeng Gu

We present a simple way to learn a transformation that maps samples of one distribution to the samples of another distribution. Our algorithm comprises an iteration of 1) drawing samples from some simple distribution and transforming them…

Machine Learning · Computer Science 2018-07-03 Joose Rajamäki , Perttu Hämäläinen