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Related papers: Second-Order Theory for Iteration Stable Tessellat…

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Since the seminal work of Mecke, Nagel and Weiss, the iteration stable (STIT) tessellations have attracted considerable interest in stochastic geometry as a natural and flexible yet analytically tractable model for hierarchical spatial…

Probability · Mathematics 2015-03-13 Tomasz Schreiber , Christoph Thaele

The intent of this paper is to describe the large scale asymptotic geometry of iteration stable (STIT) tessellations in $\mathbb{R}^d$, which form a rather new, rich and flexible class of random tessellations considered in stochastic…

Probability · Mathematics 2014-12-25 Tomasz Schreiber , Christoph Thaele

Since the seminal work by Nagel and Weiss, the iteration stable (STIT) tessellations have attracted considerable interest in stochastic geometry as a natural and flexible, yet analytically tractable model for hierarchical spatial…

Probability · Mathematics 2014-12-25 Tomasz Schreiber , Christoph Thaele

Spatially homogeneous random tessellations that are stable under iteration (nesting) in the 3-dimensional Euclidean space are considered, so-called STIT tessellations. They arise as outcome of a spatio-temporal process of subsequent cell…

Probability · Mathematics 2013-09-20 Christoph Thaele , Viola Weiss

Three-dimensional random tessellations that are stable under iteration (STIT tessellations) are considered. They arise as a result of subsequent cell division, which implies that their cells are not face-to-face. The edges of the…

Probability · Mathematics 2012-09-26 Christoph Thaele , Viola Weiss , Werner Nagel

A random recursive cell splitting scheme of the $2$-dimensional unit sphere is considered, which is the spherical analogue of the STIT tessellation process from Euclidean stochastic geometry. First-order moments are computed for a large…

Probability · Mathematics 2017-11-06 Christian Deuß , Julia Hörrmann , Christoph Thaele

In this paper planar STIT tesselations with weighted axis-parallel cutting directions are considered. They are known also as weighted planar Mondrian tesselations in the machine learning literature, where they are used in random forest…

Probability · Mathematics 2022-04-29 Carina Betken , Tom Kaufmann , Kathrin Meier , Christoph Thäle

For a class of cell division processes, generating tessellations of the Euclidean space $\mathbb{R}^d$, spatial consistency is investigated. This addresses the problem whether the distribution of these tessellations, restricted to a bounded…

Probability · Mathematics 2013-12-03 Werner Nagel , Eike Biehler

The so-called STIT tessellations form the class of homogeneous (spatially stationary) tessellations of $\mathbb{R}^d$ which are stable under the nesting/iteration operation. In this paper, we establish the strong mixing property for these…

Probability · Mathematics 2009-05-17 Raphaël Lachièze-Rey

The stable under iterated tessellation (STIT) process is a stochastic process that produces a recursive partition of space with cut directions drawn independently from a distribution over the sphere. The case of random axis-aligned cuts is…

Machine Learning · Statistics 2021-09-15 Eliza O'Reilly , Ngoc Tran

A new class of random spatial tessellations is introduced -- the so-called column tessellations of three-dimensional space. The construction is based on a stationary planar tessellation. Each cell of the spatial tessellation is a prism…

Probability · Mathematics 2014-02-20 Ngoc Linh Nguyen , Viola Weiss , Richard Cowan

We propose bending energies for isotropic elastic plates and shells. For a plate, we define and employ a surface tensor that symmetrically couples stretch and curvature such that any elastic energy density constructed from its invariants is…

Soft Condensed Matter · Physics 2022-06-22 E. Vitral , J. A. Hanna

The concept of splitting tessellations and splitting tessellation processes in spherical spaces of dimension $d\geq 2$ is introduced. Expectations, variances and covariances of spherical curvature measures induced by a splitting…

Probability · Mathematics 2018-12-03 Daniel Hug , Christoph Thaele

This paper is the second part of a two-part study of an elementary functorial construction of tesselated surfaces from finite groups. This elementary construction was discussed in the first part and generally results in a large collection…

Geometric Topology · Mathematics 2013-10-16 Mark Herman , Jonathan Pakianathan

In the setting of continuum elasticity martensitic phase transformations are characterized by a non-convex free energy density function that possesses multiple wells in strain space and includes higher-order gradient terms for…

Numerical Analysis · Mathematics 2018-05-08 Koki Sagiyama , Krishna Garikipati

The rich non-linear dynamics of the coupled oscillators (under second harmonic injection) can be leveraged to solve computationally hard problems in combinatorial optimization such as finding the ground state of the Ising Hamiltonian. While…

Optimization and Control · Mathematics 2023-10-17 Mohammad Khairul Bashar , Zongli Lin , Nikhil Shukla

A new and rather broad class of stationary (i.e. stochastically translation invariant) random tessellations of the $d$-dimensional Euclidean space is introduced, which are called shape-driven nested Markov tessellations. Locally, these…

Probability · Mathematics 2013-09-16 Tomasz Schreiber , Christoph Thaele

Tilt stability is a fundamental concept of variational analysis and optimization that plays a pivotal role in both theoretical issues and numerical computations. This paper investigates tilt stability of local minimizers for a general class…

Optimization and Control · Mathematics 2025-07-16 Boris S. Mordukhovich , Peipei Tang , Chengjing Wang

The energy-based definition provides a viable resolution to the longstanding confusion on the proper definition of $n$-th order rigidity and flexibility in geometric constraint systems. Applying an energy-based local rigidity analysis to…

Metric Geometry · Mathematics 2025-06-30 Zeyuan He

Our main objective in this paper is to develop a second-order stochastic numerical method which generalizes the well-known deterministic TR-BDF2 scheme. Since most stochastic techniques used for approximating the solution of a stochastic…

Numerical Analysis · Mathematics 2026-02-12 Tomás Caraballo , Macarena Gómez-Mármol , Ignacio Roldán
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