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In Bayesian inference, we seek to compute information about random variables such as moments or quantiles on the basis of {available data} and prior information. When the distribution of random variables is {intractable}, Monte Carlo (MC)…

Statistics Theory · Mathematics 2021-04-06 Alec Koppel , Amrit Singh Bedi , Brian M. Sadler , Victor Elvira

This paper addresses the problem of approximating an unknown function from point evaluations. When obtaining these point evaluations is costly, minimising the required sample size becomes crucial, and it is unreasonable to reserve a…

Numerical Analysis · Mathematics 2025-11-06 Nando Hegemann , Anthony Nouy , Philipp Trunschke

Deep generative models provide a systematic way to learn nonlinear data distributions, through a set of latent variables and a nonlinear "generator" function that maps latent points into the input space. The nonlinearity of the generator…

Machine Learning · Statistics 2021-12-14 Georgios Arvanitidis , Lars Kai Hansen , Søren Hauberg

Sampling a probability distribution with an unknown normalization constant is a fundamental problem in computational science and engineering. This task may be cast as an optimization problem over all probability measures, and an initial…

Machine Learning · Statistics 2024-09-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M. Stuart

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

A random field $X = (X_v)_{v \in G}$ on a quasi-transitive graph $G$ is a factor of i.i.d. if it can be written as $X=\varphi(Y)$ for some i.i.d. process $Y= (Y_v)_{v \in G}$ and equivariant map $\varphi$. Such a map, also called a coding,…

Probability · Mathematics 2022-04-11 Matan Harel , Yinon Spinka

We present the first efficient averaging sampler that achieves asymptotically optimal randomness complexity and near-optimal sample complexity. For any $\delta < \varepsilon$ and any constant $\alpha > 0$, our sampler uses $m + O(\log (1 /…

Computational Complexity · Computer Science 2025-08-18 Zhiyang Xun , David Zuckerman

We consider the sampling problem for two-sided small Fock spaces $\mathcal{F}^p_{\alpha}$, for the full range $0 < p \le \infty$. We establish a geometric description of shift-invariant sampling sequences, i.e., sequences $\Lambda$ such…

Functional Analysis · Mathematics 2025-11-27 Yurii Belov , Mikhail Mironov

We revisit, implement, and experiment with a beautiful algorithm, due to Calabi and Wilf for the random generation of subspaces over a finie field.

Combinatorics · Mathematics 2023-10-30 Shalosh B. Ekhad , Doron Zeilberger

For any $d \geq 1$, random $\mathbb{Z}^d$ shifts of finite type (SFTs) were defined in previous work of the authors. For a parameter $\alpha \in [0,1]$, an alphabet $\mathcal{A}$, and a scale $n \in \mathbb{N}$, one obtains a distribution…

Dynamical Systems · Mathematics 2017-05-02 Kevin McGoff , Ronnie Pavlov

The structure of certain types of quasi shift-invariant spaces, which take the form $V(\psi,\mathcal{X}):=\overline{\text{span}}^{L_2}\{\psi(\cdot-x_j):j\in\mathbb{Z}\}$ for a discrete set $\mathcal{X}=(x_j)\subset\mathbb{R}$ is…

Functional Analysis · Mathematics 2018-02-14 Keaton Hamm , Jeff Ledford

Group-invariant probability distributions appear in many data-generative models in machine learning, such as graphs, point clouds, and images. In practice, one often needs to estimate divergences between such distributions. In this work, we…

Machine Learning · Computer Science 2026-02-05 Behrooz Tahmasebi , Stefanie Jegelka

The possibility of mass in the context of scale-invariant, generally covariant theories, is discussed. Scale invariance is considered in the context of a gravitational theory where the action, in the first order formalism, is of the form $S…

High Energy Physics - Theory · Physics 2009-11-07 E. I. Guendelman

We consider a class of real numbers, a subset of irrational numbers and certain mathematical constants, for which the elements in the simple continued fraction appears to be random. As an illustrative example, one can consider $\pi = \{x_0,…

Statistical Mechanics · Physics 2020-02-19 Avinash Chand Yadav

Scale invariance is considered in the context of gravitational theories where the action, in the first order formalism, is of the form $S = \int L_{1} \Phi d^4x$ + $\int L_{2}\sqrt{-g}d^4x$ where the volume element $\Phi d^4x$ is…

High Energy Physics - Theory · Physics 2007-05-23 E. I. Guendelman

We propose a new generator for the generalized inverse Gaussian (GIG) distribution by decomposing the density of GIG into two components. The first component is a truncated inverse Gamma density, in order to sample from which we improve the…

Computation · Statistics 2022-11-24 Xiaozhu Zhang , Jerome P. Reiter

This paper demonstrates that random, independently chosen equi-dimensional subspaces with a unitarily invariant distribution in a real Hilbert space provide nearly tight, nearly equiangular fusion frames. The angle between a pair of…

Functional Analysis · Mathematics 2013-03-26 Bernhard G. Bodmann

We study the problem of sampling from a distribution $\mu$ with density $\propto e^{-V}$ for some potential function $V:\mathbb R^d\to \mathbb R$ with query access to $V$ and $\nabla V$. We start with the following standard assumptions: (1)…

Data Structures and Algorithms · Computer Science 2026-02-10 Yuchen He , Zhehan Lei , Jianan Shao , Chihao Zhang

In this work we propose a new analytical method for determining the scalar field potential $V(\phi)$ in FRW type cosmologies containing a mixture of perfect fluid plus a quintessence scalar field. By assuming that the equation of state…

General Relativity and Quantum Cosmology · Physics 2008-06-23 J. A. Espichán Carrillo , J. M. Silva , J. A. S. Lima

We study the random sampling of the short-time Fourier transform of functions that are localized in a compact region in the time-frequency plane. We follow the approach introduced by Bass and Gr\"ochenig for band-limited functions, and show…

Functional Analysis · Mathematics 2017-08-01 Gino Angelo Velasco