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This paper investigates the problem of Gaussian approximation for the wireless multi-access interference distribution in large spatial wireless networks. First, a principled methodology is presented to establish rates of convergence of the…

Probability · Mathematics 2015-06-04 Hazer Inaltekin

It is often convenient to use Gaussian blur in studying image quality or in data augmentation pipelines for training convoluional neural networks. Because of their convenience, Guassians are sometimes used as first order approximations of…

Image and Video Processing · Electrical Eng. & Systems 2023-01-04 Austin C. Bergstrom , David Conran , David W. Messinger

We summarize the parallel session B4: 'Analytic approximations, perturbation theory effective field theory methods and their applications' and the joint session B2/B4: 'Approximate solutions to Einstein equations: Methods and Applications',…

General Relativity and Quantum Cosmology · Physics 2015-06-18 Vitor Cardoso , Rafael A. Porto

Context. Whenever correlation functions are used for inference about cosmological parameters in the context of a Bayesian analysis, the likelihood function of correlation functions needs to be known. Usually, it is approximated as a…

Cosmology and Nongalactic Astrophysics · Physics 2013-08-06 Philipp Wilking , Peter Schneider

We show under general assumptions that the mean-field approximation for quan- tum many-boson systems is correct. Our contribution unifies and improves on most of the known results. The proof uses general properties of quantization in…

Mathematical Physics · Physics 2017-01-11 Quentin Liard

We analyze the Gaussian approximation as a method to obtain the first and second moments of a stochastic process described by a master equation. We justify the use of this approximation with ideas coming from van Kampen's expansion approach…

Statistical Mechanics · Physics 2015-05-18 Luis F. Lafuerza , Raul Toral

The structure of the gaussian auxiliary field approximation in the theory of phase ordering kinetics is analysed with the aim of placing the method within the context of a systematic theory. While we are unable to do this for systems with a…

Condensed Matter · Physics 2016-08-31 De Siena , M. Zannetti

In this article, we obtain a super-exponential rate of convergence in total variation between the traces of the first $m$ powers of an $n\times n$ random unitary matrices and a $2m$-dimensional Gaussian random variable. This generalizes…

Probability · Mathematics 2020-02-06 Kurt Johansson , Gaultier Lambert

In this article we give a general criterion for some dependent Gaussian models to belong to maximal domain of attraction of Gumbel, following an application of the Stein-Chen method studied in Arratia et al(1989). We also show the…

Probability · Mathematics 2016-11-03 Alberto Chiarini , Alessandra Cipriani , Rajat Subhra Hazra

The truncation scheme dependence of the exact renormalization group equations is investigated for scalar field theories in three dimensions. The exponents are numerically estimated to the next-to-leading order of the derivative expansion.…

High Energy Physics - Theory · Physics 2009-10-31 Ken-Ichi Aoki , Keiichi Morikawa , Wataru Souma , Jun-Ichi Sumi , Haruhiko Terao

Gaussian processes are a powerful class of non-linear models, but have limited applicability for larger datasets due to their high computational complexity. In such cases, approximate methods are required, for example, the recently…

Methodology · Statistics 2026-03-24 Soham Mukherjee , Manfred Claassen , Paul-Christian Bürkner

Variational approximation methods have proven to be useful for scaling Bayesian computations to large data sets and highly parametrized models. Applying variational methods involves solving an optimization problem, and recent research in…

Methodology · Statistics 2017-01-13 Victor M. -H. Ong , David J. Nott , Michael S. Smith

We focus on the behavior of (2+1)d $\lambda\phi^4$ and (5+1)d $\lambda\phi^3$ or $\lambda|\phi|^3$ theories in different regimes and compare the results obtained from the adaptive perturbation method with those obtained from lattice…

High Energy Physics - Theory · Physics 2024-11-12 Chen-Te Ma , Hui Zhang

Mean field approximation is a popular method to study the behaviour of stochastic models composed of a large number of interacting objects. When the objects are asynchronous, the mean field approximation of a population model can be…

Performance · Computer Science 2018-07-24 Nicolas Gast , Diego Latella , Mieke Massink

We propose an adaptive importance sampling scheme for Gaussian approximations of intractable posteriors. Optimization-based approximations like variational inference can be too inaccurate while existing Monte Carlo methods can be too slow.…

Computation · Statistics 2025-02-04 Willem van den Boom , Andrea Cremaschi , Alexandre H. Thiery

The usual renormalization procedure for the variational approximation with a trial Gaussian ansatz for the $\lap$ model in 3+1 dimensions is re-analysed as a departing framework for the investigation of the parameters of the model. The…

High Energy Physics - Phenomenology · Physics 2015-07-03 Fabio L. Braghin

We prove that the scaling limits of spin fluctuations in four-dimensional Ising-type models with nearest-neighbor ferromagnetic interaction at or near the critical point are Gaussian. A similar statement is proven for the $\lambda \phi^4$…

Mathematical Physics · Physics 2022-01-25 Michael Aizenman , Hugo Duminil-Copin

We solve isotropic, homogeneous cosmological models containing a self-interacting scalar field. Calculations are performed in four and two-dimensional spacetimes. We find several exact solutions that have an inflationary regime or has a…

General Relativity and Quantum Cosmology · Physics 2012-08-07 Luis P. Chimento , Adriana E. Cossarini , Alejandro S. Jakubi

The dynamics of non-equilibrium Ising model with parallel updates is investigated using a generalized mean field approximation that incorporates multiple two-site correlations at any two time steps, which can be obtained recursively. The…

Disordered Systems and Neural Networks · Physics 2015-06-17 Hamed Mahmoudi , David Saad

In this paper, we use some standard numerical techniques to approximate the hypergeometric function $$ {}_2F_1[a,b;c;x]=1+\frac{ab}{c}x+\frac{a(a+1)b(b+1)}{c(c+1)}\frac{x^2}{2!}+\cdots $$ for a range of parameter triples $(a,b,c)$ on the…

Numerical Analysis · Mathematics 2017-07-26 Hina Manoj Arora , Swadesh Kumar Sahoo