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Universal conductance fluctuations are usually observed in the form of aperiodic oscillations in the magnetoresistance of thin wires as a function of the magnetic field B. If such oscillations are completely random at scales exceeding…

Disordered Systems and Neural Networks · Physics 2021-12-28 I. M. Suslov

We develop a privatised stochastic variational inference method for Latent Dirichlet Allocation (LDA). The iterative nature of stochastic variational inference presents challenges: multiple iterations are required to obtain accurate…

Machine Learning · Statistics 2018-12-05 Mijung Park , James Foulds , Kamalika Chaudhuri , Max Welling

We consider a class of tempered subordinators, namely a class of subordinators with one-dimensional marginal tempered distributions which belong to a family studied in [3]. The main contribution in this paper is a non-central moderate…

Probability · Mathematics 2020-11-05 Nikolai Leonenko , Claudio Macci , Barbara Pacchiarotti

The motion of oscillatory-like nonlinear Hamiltonian systems, driven by a weak noise, is considered. A general method to find regions of stability in the phase space of a randomly-driven system, based on a specific Poincar\'e map, is…

Chaotic Dynamics · Physics 2011-11-10 D. V. Makarov , M. Yu. Uleysky , M. V Budyansky , S. V. Prants

Testing for white noise is a classical yet important problem in statistics, especially for diagnostic checks in time series modeling and linear regression. For high-dimensional time series in the sense that the dimension $p$ is large in…

Statistics Theory · Mathematics 2018-11-26 Zeng Li , Clifford Lam , Jianfeng Yao , Qiwei Yao

We explore an asymptotic behavior of densities of sums of independent random variables that are convoluted with a small continuous noise.

Probability · Mathematics 2019-01-11 Sergey G. Bobkov , Arnaud Marsiglietti

We analyze the strong noise limit of one-dimensional stochastic differential equations (SDEs). Our initial motivation comes from continuous measurements of open quantum systems. In this context, Bauer, Bernard and Tilloy pointed out an…

Discrete prompts have been used for fine-tuning Pre-trained Language Models for diverse NLP tasks. In particular, automatic methods that generate discrete prompts from a small set of training instances have reported superior performance.…

Computation and Language · Computer Science 2023-02-14 Yoichi Ishibashi , Danushka Bollegala , Katsuhito Sudoh , Satoshi Nakamura

We consider a chain of weakly harmonic coupled oscillators perturbed by a conservative noise. We show that by tuning accordingly the coupling constant energy can diffuse like a Brownian motion or superdiffuse like a maximally 3/2-stable…

Probability · Mathematics 2016-11-10 Cedric Bernardin , Patricia Goncalves , Milton Jara

The aim of this paper is to present a result of discrete approximation of some class of stable self-similar stationary increments processes. The properties of such processes were intensively investigated, but little is known on the context…

Probability · Mathematics 2008-01-18 Clément Dombry , Nadine Guillotin-Plantard

Using the Bismut's approach to Malliavin calculus, we introduce a simplified Malliavin matrix ([11]) for stochastic differential equations (SDEs) force by degenerate stable like noises. For the degenerate SDEs driven by Wiener noises, one…

Probability · Mathematics 2014-02-21 Lihu Xu

We present a new type of deterministic dynamical behaviour that is less predictable than white noise. We call it anti-deterministic (AD) because time series corresponding to the dynamics of such systems do not generate deterministic lines…

Statistical Mechanics · Physics 2009-11-10 Krzysztof Urbanowicz , Holger Kantz , Janusz A. Holyst

The theory of sparse stochastic processes offers a broad class of statistical models to study signals. In this framework, signals are represented as realizations of random processes that are solution of linear stochastic differential…

Probability · Mathematics 2017-02-17 Julien Fageot , Virginie Uhlmann , Michael Unser

Classical diffusion models typically rely on isotropic Gaussian noise, treating all regions uniformly and overlooking structural information important for high-quality generation. We introduce an edge-preserving diffusion process that…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Jente Vandersanden , Sascha Holl , Xingchang Huang , Gurprit Singh

It is well-known that density estimation on the unit interval is asymptotically equivalent to a Gaussian white noise experiment, provided the densities have H\"older smoothness larger than $1/2$ and are uniformly bounded away from zero. We…

Statistics Theory · Mathematics 2018-10-29 Kolyan Ray , Johannes Schmidt-Hieber

We present a general method to construct couplings of stochastic differential equations driven by L\'{e}vy noise in terms of coupling operators. This approach covers both coupling by reflection and refined basic coupling which are often…

Probability · Mathematics 2018-11-22 Mingjie Liang , René L. Schilling , Jian Wang

A continuous-time nonlinear regression model with L\'evy-driven linear noise process is considered. Sufficient conditions of consistency and asymptotic normality of the Whittle estimator for the parameter of the noise spectral density are…

Probability · Mathematics 2019-09-24 A. V. Ivanov , N. N. Leonenko , I. V. Orlovskyi

We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the statevector, white noise stochastic processes with non white ones. We prove that such a modification can be consistently…

Quantum Physics · Physics 2009-11-07 Angelo Bassi , GianCarlo Ghirardi

Traveling waves are ubiquitous in nature and control the speed of many important dynamical processes, including chemical reactions, epidemic outbreaks, and biological evolution. Despite their fundamental role in complex systems, traveling…

Populations and Evolution · Quantitative Biology 2011-05-30 Oskar Hallatschek

We consider the inverse problem of recovering a continuous-domain function from a finite number of noisy linear measurements. The unknown signal is modeled as the sum of a slowly varying trend and a periodic or quasi-periodic seasonal…

Functional Analysis · Mathematics 2025-05-16 Julien Fageot
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