arXiv research

Given a set of points that sample a shape, the Rips complex of the data points is often used in machine-learning to provide an approximation of the shape easily-computed. It has been proved recently that the Rips complex captures the homotopy type of the shape assuming the vertices of the complex meet some mild samplin…

Unique inhomogeneous ruled hypersurface found in complex hyperbolic space.

An important "stability" theorem in shape theory, due to D.A. Edwards and R. Geoghegan, characterizes those compacta having the same shape as a finite CW complex. In this note we present straightforward and self-contained proof of that theorem.

Optimizes shapes in uncertain Navier-Stokes flow problems.

Study shows some complex shapes don't fit a certain property.

Space mapping speeds up shape optimization for PDEs.

In this paper, we obtain some properties of biconservative Lorentz hypersurface $M_{1}^{n}$ in $E_{1}^{n+1}$ having shape operator with complex eigen values. We prove that every biconservative Lorentz hypersurface $M_{1}^{n}$ in $E_{1}^{n+1}$ whose shape operator has complex eigen values with at most five distinct prin…

In his paper "Shapes of Polyhedra and Triangulations of the Sphere", Thurston found that the set of shapes of convex polyhedra with prescribed cone-deficits has a complex hyperbolic structure. Inspired by his work, this paper studies the set of shapes of centrally symmetric octahedra with prescribed cone-deficits. We s…

Classifies shapes of yield curves in the Svensson family.

This article introduces vortex nerve complexes in CW (Closure finite Weak) topological spaces, which first appeared in works by P. Alexandroff, H. Hopf and J.H.C. Whitehead during the 1930s. A vortex nerve is a CW complex containing one or more intersecting path-connected cycles. Each vortex nerve has its own distincti…

Python tools for 3D shape analysis on Kendall's space.

New connection found between shape reconstruction methods and persistent homology.

Study on real hypersurfaces in products of complex space forms, proving rigidity and nonexistence results.

New algorithms reduce rejection sampling complexity for shape-constrained distributions.

The space of shapes of a polyhedron with given total angles less than 2πat each of its n vertices has a Kaehler metric, locally isometric to complex hyperbolic space CH^{n-3}. The metric is not complete: collisions between vertices take place a finite distance from a nonsingular point. The metric completion is a comple…

Paper analyzes shapes of brain arterial networks using statistical methods.

A language for specifying complex reinforcement learning tasks.

Let M be a CR submanifold of maximal CR dimension of a complex space form M. The shape operator A of the distinguished vector field ξ is recurrent if there exists a 1-form v such that \nabla A = A \otimes v. We show that M is an Euclidean space under the condition that A is recurrent.

New method generates optical vortices in any knot shape.

Complex functional maps link tangent bundles, preserving orientation and angles.

Analyze and predict complex 3D shape deformations using LSTM autoencoders and oriented bounding boxes.

Large prospective epidemiological studies acquire cardiovascular magnetic resonance (CMR) images for pre-symptomatic populations and follow these over time. To support this approach, fully automatic large-scale 3D analysis is essential. In this work, we propose a novel deep neural network using both CMR images and pati…

This article introduces planar shape signatures derived from homology nerves, which are intersecting 1-cycles in a collection of homology groups endowed with a proximal relator (set of nearness relations) that includes a descriptive proximity. A 1-cycle is a closed, connected path with a zero boundary in a simplicial c…

The paper shows how to use fine shape to understand infinite-dimensional spaces.

Extended orbit model theory for shape analysis using graded group action framework.

New deep learning method preserves orientation in shape matching.

New proof for complex 3D shapes.

A framework for generating 3D shapes by sequentially assembling primitives.

In the elastic shape analysis approach to shape matching and object classification, plane curves are represented as points in an infinite-dimensional Riemannian manifold, wherein shape dissimilarity is measured by geodesic distance. A remarkable result of Younes, Michor, Shah and Mumford says that the space of closed p…

TLRS improves predictive power of mined formulaic alpha factors.

Study examines heart and football-shaped metrics, verifying geometric structure.

Bézier-GAN optimizes airfoil design by reducing shape complexity.

We use matrix iteration theory to characterize acceleration in smooth games. We define the spectral shape of a family of games as the set containing all eigenvalues of the Jacobians of standard gradient dynamics in the family. Shapes restricted to the real line represent well-understood classes of problems, like minimi…

New framework classifies high-dimensional shapes using ray intersections, establishing data requirements.

Fine shape theory extends strong shape to noncompact metrizable spaces.

Stark hypersurfaces are a special class of austere hypersurface in ${\mathbb C}P^n$ where the shape operator is compatible with the $CR$-structure. In this paper, the possible shape operators for stark hypersurfaces are completely determined, and stark hypersurfaces in ${\mathbb C}P^2$ are constructed as integrals of a…

A registration-free framework monitors shape and color in 4D point clouds.

The success of various applications including robotics, digital content creation, and visualization demand a structured and abstract representation of the 3D world from limited sensor data. Inspired by the nature of human perception of 3D shapes as a collection of simple parts, we explore such an abstract shape represe…

Bayesian nonparametric method partitions shapes using curves.

Study efficient geodesics in curve complex using dot graphs.

We study Lorentz hypersurfaces $M_{1}^{n}$ in $E_{1}^{n+1}$ satisfying $\triangle \vec {H}= α\vec {H}$ with non diagonal shape operator, having complex eigenvalues. We prove that every such Lorentz hypersurface in $E_{1}^{n+1}$ having at most five distinct principal curvatures has constant mean curvature.

We consider the evolution by inverse mean curvature flow of a closed, mean convex and star-shaped hypersurface in the complex hyperbolic space. We prove that the flow is defined for any positive time, the evolving hypersurface stays star-shaped and mean convex. Moreover the induced metric converges, after rescaling, to…

For dynamical systems that can be modelled as asymptotically stable linear systems forced by Gaussian noise, this paper develops methods to infer or estimate their modes from observations in real time. The modes can be real or complex. For a real mode, we wish to infer its damping rate and mode shape. For a complex mod…

Functional BART adds shape priors to Bayesian tree regression for better curve fitting.

Generative model learns shape drift for quantifying domain uncertainty in hemodynamics.

WDAIL uses Wasserstein distance for more effective reward shaping in IL.

We introduce and begin to explore the mean and median of finite sets of shapes represented as integral currents. The median can be computed efficiently in practice, and we focus most of our theoretical and computational attention on medians. We consider questions on the existence and regularity of medians. While the me…

Convolutional Neural Networks (CNNs) are commonly thought to recognise objects by learning increasingly complex representations of object shapes. Some recent studies suggest a more important role of image textures. We here put these conflicting hypotheses to a quantitative test by evaluating CNNs and human observers on…