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This article presents a new class of Pseudorandom Number Generators. The generators are based on traversing a n-cube where a Balanced Hamiltonian Cycle has been removed. The construction of such generators is automatic for small number of…

Data Structures and Algorithms · Computer Science 2017-06-28 Jean-François Couchot , Pierre-Cyrille Heam , Christophe Guyeux , Qianxue Wang , Jacques M. Bahi

In regular dynamics, discrete maps are model presentations of discrete dynamical systems, and they may approximate continuous dynamical systems. Maps are used to investigate general properties of dynamical systems and to model various…

Chaotic Dynamics · Physics 2024-12-31 Mark Edelman

Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators…

Quantum Physics · Physics 2026-04-02 Anurag K. S. V. , Shubham Chouhan , K. Srinivasan , G. Raghavan , Kanaka Raju P

The paper study counter-dependent pseudorandom generators; the latter are generators such that their state transition function (and output function) is being modified dynamically while working: For such a generator the recurrence sequence…

Cryptography and Security · Computer Science 2011-11-15 Vladimir Anashin

In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discards a large part of training data, we show provable guarantees…

Machine Learning · Statistics 2019-01-29 Kohei Hayashi , Masaaki Imaizumi , Yuichi Yoshida

The prime numbers look like a randomly chosen sequence of natural numbers, but there is still no strict theory to determine 'Randomness'. In these years, cryptography has developed a battery of statistical tests for randomness. In this…

Number Theory · Mathematics 2011-02-19 Wang Liang , Huang Yan

Kernel approximation using randomized feature maps has recently gained a lot of interest. In this work, we identify that previous approaches for polynomial kernel approximation create maps that are rank deficient, and therefore do not…

Machine Learning · Statistics 2013-12-18 Raffay Hamid , Ying Xiao , Alex Gittens , Dennis DeCoste

Pi Fractions are used to create deterministic uniformly distributed pseudorandom decision space sample points for a global search and optimization algorithm. These fractions appear to be uniformly distributed on [0,1] and can be used in any…

Other Computer Science · Computer Science 2014-03-18 Richard A. Formato

Web-based services often run randomized experiments to improve their products. A popular way to run these experiments is to use geographical regions as units of experimentation, since this does not require tracking of individual users or…

Social and Information Networks · Computer Science 2019-02-19 David Rolnick , Kevin Aydin , Jean Pouget-Abadie , Shahab Kamali , Vahab Mirrokni , Amir Najmi

We develop a pseudo-random generator to fool degree-$d$ polynomial threshold functions with respect to the Gaussian distribution. For $c>0$ any constant, we construct a pseudo-random generator that fools such functions to within $\epsilon$…

Computational Complexity · Computer Science 2011-04-08 Daniel M. Kane

Gluing theorem for random unitaries [Schuster, Haferkamp, Huang, QIP 2025] have found numerous applications, including designing low depth random unitaries [Schuster, Haferkamp, Huang, QIP 2025], random unitaries in ${\sf QAC0}$ [Foxman,…

Cryptography and Security · Computer Science 2025-10-07 Prabhanjan Ananth , John Bostanci , Aditya Gulati , Yao-Ting Lin

Recent methods for conditional image generation benefit from dense supervision such as segmentation label maps to achieve high-fidelity. However, it is rarely explored to employ dense supervision for unconditional image generation. Here we…

Computer Vision and Pattern Recognition · Computer Science 2022-07-28 Gayoung Lee , Hyunsu Kim , Junho Kim , Seonghyeon Kim , Jung-Woo Ha , Yunjey Choi

This paper addresses the Bayesian calibration of dynamic models with parametric and structural uncertainties, in particular where the uncertain parameters are unknown/poorly known spatio-temporally varying subsystem models. Independent…

Computation · Statistics 2012-11-02 Piyush Tagade , Han-Lim Choi

In recent years, a lot of research has gone into creating multi-layer chaotic mapping-based cryptosystems. Random-like behavior, a continuous broadband power spectrum, and a weak baseline condition dependency are all characteristics of…

Cryptography and Security · Computer Science 2022-08-15 Awnon Bhowmik , Emon Hossain , Mahmudul Hasan

We propose methods for constructing high-quality pseudorandom number generators (RNGs) based on an ensemble of hyperbolic automorphisms of the unit two-dimensional torus (Sinai-Arnold map or cat map) while keeping a part of the information…

Computational Physics · Physics 2009-04-02 L. Barash , L. N. Shchur

Generative AutoEncoders require a chosen probability distribution in latent space, usually multivariate Gaussian. The original Variational AutoEncoder (VAE) uses randomness in encoder - causing problematic distortion, and overlaps in latent…

Machine Learning · Computer Science 2019-01-15 Jarek Duda

In a recent paper (Asci \textit{et al.}, 2008) it has been shown that certain random continued fractions have a density which is a product of a beta density and a hypergeometric function $_{2}F_{1}$. In the present paper we fully exploit a…

Probability · Mathematics 2010-04-09 Gérard Letac , Mauro Piccioni

Sequence generators obtained by linear recursions over the two-element field $\mathbb{F}_2$, i.e., $\mathbb{F}_2$-linear generators, are widely used as pseudorandom number generators. For example, the Mersenne Twister MT19937 is one of the…

Numerical Analysis · Computer Science 2016-06-21 Shin Harase

This paper is the first work to propose a network to predict a structured uncertainty distribution for a synthesized image. Previous approaches have been mostly limited to predicting diagonal covariance matrices. Our novel model learns to…

Machine Learning · Statistics 2026-05-14 Gara Dorta , Sara Vicente , Lourdes Agapito , Neill D. F. Campbell , Ivor Simpson

Recent exact analytical results developed for the random number generators with taps are reported. These results are applicable to a wide class of algorithms, including random walks, cluster algorithms, Ising models. Practical…

High Energy Physics - Lattice · Physics 2009-11-07 Lev N. Shchur