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This work deals with the simulation of Wishart processes and affine diffusions on positive semidefinite matrices. To do so, we focus on the splitting of the infinitesimal generator, in order to use composition techniques as Ninomiya and…

Probability · Mathematics 2013-03-14 Abdelkoddousse Ahdida , Aurélien Alfonsi

The long-term distributions of trajectories of a flow are described by invariant densities, i.e. fixed points of an associated transfer operator. In addition, global slowly mixing structures, such as almost-invariant sets, which partition…

Numerical Analysis · Mathematics 2015-03-17 Gary Froyland , Oliver Junge , Péter Koltai

A characterization of finitely generated shift-invariant subspaces is given when generators are g-minimal. An algorithm is given for the determination of the coefficients in the well known representation of the Fourier transform of an…

Classical Analysis and ODEs · Mathematics 2019-06-18 K. S. Kazarian

Molecular conformation generation, a critical aspect of computational chemistry, involves producing the three-dimensional conformer geometry for a given molecule. Generating molecular conformation via diffusion requires learning to reverse…

Computational Physics · Physics 2023-10-10 Zihan Zhou , Ruiying Liu , Chaolong Ying , Ruimao Zhang , Tianshu Yu

We provide a new representation of a refinable shift invariant space with a compactly supported generator, in terms of functions with a special property of homogeneity. In particular these functions include all the homogeneous polynomials…

Classical Analysis and ODEs · Mathematics 2007-05-23 Carlos Cabrelli , Sigrid Heineken , Ursula Molter

Given a set of $n$ sites from $\mathbb{R}^d$, each having some positive weight factor, the Multiplicatively Weighted Voronoi Diagram is a subdivision of space that associates each cell to the site whose weighted Euclidean distance is…

Computational Geometry · Computer Science 2024-03-19 Joachim Gudmundsson , Martin P. Seybold , Sampson Wong

This paper considers the iterative solution of linear systems arising from discretization of the anisotropic radiative transfer equation with discontinuous elements on the sphere. In order to achieve robust convergence behavior in the…

Numerical Analysis · Mathematics 2021-03-11 Jürgen Dölz , Olena Palii , Matthias Schlottbom

We study the properties of the set of marginal distributions of infinite translation-invariant systems in the 2D square lattice. In cases where the local variables can only take a small number $d$ of possible values, we completely solve the…

Mathematical Physics · Physics 2018-09-26 Zizhu Wang , Miguel Navascués

Convergence rates of kernel density estimators for stationary time series are well studied. For invertible linear processes, we construct a new density estimator that converges, in the supremum norm, at the better, parametric, rate…

Statistics Theory · Mathematics 2009-09-29 Anton Schick , Wolfgang Wefelmeyer

A Voronoi diagram partitions the plane into convex cells, each containing the points closest to a single generator. Given such a tessellation, the inverse Voronoi problem seeks the generator set \( S \) that produced it. Our algorithm…

Metric Geometry · Mathematics 2025-06-25 Carlos M Hernandez-Suarez

Relativistic beams of heavy ions interacting with various nuclear targets allow to study a broad range of problems starting from nuclear equation of state to the traditional nuclear structure. Some questions which were impossible to answer…

Nuclear Theory · Physics 2024-07-09 A. B. Larionov , Yu. N. Uzikov

We investigate the conformal algebra on the fuzzy sphere, and in particular the generators of translations and special conformal transformations which are emergent symmetries in the infinite IR but are broken along the RG flow. We show how…

High Energy Physics - Theory · Physics 2025-08-22 Giulia Fardelli , A. Liam Fitzpatrick , Emanuel Katz

We aim at estimating in a non-parametric way the density $\pi$ of the stationary distribution of a $d$-dimensional stochastic differential equation $(X_t)_{t \in [0, T]}$, for $d \ge 2$, from the discrete observations of a finite sample…

Statistics Theory · Mathematics 2022-12-29 Chiara Amorino , Arnaud Gloter

This paper, broadly speaking, covers the use of randomness in two main areas: low-rank approximation and kernel methods. Low-rank approximation is very important in numerical linear algebra. Many applications depend on matrix decomposition…

Numerical Analysis · Mathematics 2020-08-12 Rishi Advani , Madison Crim , Sean O'Hagan

To accelerate kernel methods, we propose a near input sparsity time algorithm for sampling the high-dimensional feature space implicitly defined by a kernel transformation. Our main contribution is an importance sampling method for…

Data Structures and Algorithms · Computer Science 2020-07-15 David P. Woodruff , Amir Zandieh

Quadratic harnesses are time-inhomogeneous Markov polynomial processes with linear conditional expectations and quadratic conditional variances with respect to the past-future filtrations. Typically they are determined by five numerical…

Probability · Mathematics 2024-01-23 Jacek Wesołowski , Agnieszka Zięba

Scalable safety verification of continuous state dynamic systems has been demonstrated through both reachability and viability analyses using parametric set representations; however, these two analyses are not interchangable in practice for…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Ian M. Mitchell , Jacob Budzis , Andriy Bolyachevets

This work is motivated by the need of efficient numerical simulations of gas flows in the serpentine channels used in proton-exchange membrane fuel cells. In particular, we consider the Poisson problem in a 2D domain composed of several…

Numerical Analysis · Mathematics 2023-12-14 Hussein Albazzal , Alexei Lozinski , Roberta Tittarelli

Even simply-defined, finite-state generators produce stochastic processes that require tracking an uncountable infinity of probabilistic features for optimal prediction. For processes generated by hidden Markov chains the consequences are…

Statistical Mechanics · Physics 2021-09-15 Alexandra M. Jurgens , James P. Crutchfield

A method is presented for accelerating inference in transformer language models by exploiting the low effective rank of the token activation manifold at each layer. The method decomposes each activation vector into a subspace component and…

Machine Learning · Computer Science 2026-05-06 Stephen J. Thomas
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