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We consider the exponential functional $A_{\infty}=\int_0^{\infty} e^{\xi_s} ds$ associated to a Levy process $(\xi_t)_{t \geq 0}$. We find the asymptotic behavior of the tail of this random variable, under some assumptions on the process…

Probability · Mathematics 2007-05-23 Mejane Olivier

Diffusion models, which convert noise into new data instances by learning to reverse a diffusion process, have become a cornerstone in contemporary generative modeling. In this work, we develop non-asymptotic convergence theory for a…

Machine Learning · Computer Science 2024-08-06 Gen Li , Yuting Wei , Yuejie Chi , Yuxin Chen

Many enumeration problems in combinatorics, including such fundamental questions as the number of regular graphs, can be expressed as high-dimensional complex integrals. Motivated by the need for a systematic study of the asymptotic…

Combinatorics · Mathematics 2017-12-29 Mikhail Isaev , Brendan D. McKay

Diffusion models, which convert noise into new data instances by learning to reverse a Markov diffusion process, have become a cornerstone in contemporary generative modeling. While their practical power has now been widely recognized, the…

Machine Learning · Statistics 2024-03-08 Gen Li , Yuting Wei , Yuxin Chen , Yuejie Chi

In empirical studies, the data usually don't include all the variables of interest in an economic model. This paper shows the identification of unobserved variables in observations at the population level. When the observables are distinct…

Econometrics · Economics 2022-12-07 Yingyao Hu

In this paper we study empirical measures which can be thought as a decoupled version of the empirical measures generated by random matrices. We prove the large deviation principle with the rate function, which is finite only on product…

Probability · Mathematics 2007-05-23 Wlodek Bryc

In all local low-dimensional models, scaling at critical points deviates from mean field behavior -- with one possible exception. This exceptional model with ``ordinary" behavior is an inherently non-equilibrium model studied some time ago…

Statistical Mechanics · Physics 2022-02-16 Peter Grassberger

A $d$-dimensional nonparametric additive regression model with dependent observations is considered. Using the marginal integration technique and wavelets methodology, we develop a new adaptive estimator for a component of the additive…

Statistics Theory · Mathematics 2012-08-07 Christophe Chesneau , Jalal M. Fadili , Bertrand Maillot

In this paper a differential equation with noninteger order was used to model an anomalous luminescence decay process. Although this process is in principle an exponential decaying process, recent data indicates that is not the case for…

Statistical Mechanics · Physics 2016-07-05 Nelson H. T. Lemes , José Paulo C. dos Santos , João P. Braga

By considering a lattice model of extended phase space, and using techniques of noncommutative differential geometry, we are led to: (a) the conception of vector fields as generators of motion and transition probability distributions on the…

Mathematical Physics · Physics 2014-11-18 A. Dimakis , C. Tzanakis

We show that when a high-dimensional data matrix is the sum of a low-rank matrix and a random error matrix with independent entries, the low-rank component can be consistently estimated by solving a convex minimization problem. We develop a…

Econometrics · Economics 2019-11-14 Jushan Bai , Junlong Feng

We consider nonparametric Bayesian inference in a multidimensional diffusion model with reflecting boundary conditions based on discrete high-frequency observations. We prove a general posterior contraction rate theorem in $L^2$-loss, which…

Statistics Theory · Mathematics 2025-08-12 Marc Hoffmann , Kolyan Ray

We study the problem of estimating a mean pattern from a set of similar curves in the setting where the variability in the data is due to random geometric deformations and additive noise. We propose an estimator based on the notion of…

Statistics Theory · Mathematics 2013-06-12 Jérémie Bigot , Xavier Gendre

We study statistical inference for small-noise-perturbed multiscale dynamical systems under the assumption that we observe a single time series from the slow process only. We construct estimators for both averaging and homogenization…

Probability · Mathematics 2018-09-13 Siragan Gailus , Konstantinos Spiliopoulos

We study the asymptotic shape of the trajectory of the stochastic gradient descent algorithm applied to a convex objective function. Under mild regularity assumptions, we prove a functional central limit theorem for the properly rescaled…

Machine Learning · Statistics 2026-02-18 Kessang Flamand , Victor-Emmanuel Brunel

The distribution of return intervals of extreme events is studied in time series characterized by finite-term correlations with non-exponential decay. Precisely, it has been analyzed the statistics of the return intervals of extreme values…

Data Analysis, Statistics and Probability · Physics 2009-11-11 Cecilia Pennetta

Regression models for limited continuous dependent variables having a non-negligible probability of attaining exactly their limits are presented. The models differ in the number of parameters and in their flexibility. Fractional data being…

Applications · Statistics 2012-05-31 Fabio Sigrist , Werner A. Stahel

We show that the scaled cumulant generating and large deviation function, associated to a two-state Markov process involving two processes, obey a symmetry relation reminiscent of the fluctuation theorem, independent from any conditions on…

Statistical Mechanics · Physics 2015-06-19 Tim Willaert , Bart Cleuren , Christian Van den Broeck

A notion of stochastic deformation is introduced and the corresponding algebraic deformation procedure is developed. This procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an…

Statistical Mechanics · Physics 2008-04-19 P. O. Kazinski

Exotic stochastic processes are shown to emerge in the quantum evolution of complex systems. Using influence function techniques, we consider the dynamics of a system coupled to a chaotic subsystem described through random matrix theory. We…

chao-dyn · Physics 2009-10-31 Dimitri Kusnezov , Aurel Bulgac , Giu Do Dang