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In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification.…

Computation · Statistics 2026-05-01 Jingning Yao , Ajay Jasra , Sheng Jiang

Diffusion models have recently exhibited remarkable abilities to synthesize striking image samples since the introduction of denoising diffusion probabilistic models (DDPMs). Their key idea is to disrupt images into noise through a fixed…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Zijian Zhang , Zhou Zhao , Jun Yu , Qi Tian

Diffusion models have recently shown considerable potential in solving Bayesian inverse problems when used as priors. However, sampling from the resulting denoising posterior distributions remains a challenge as it involves intractable…

Machine Learning · Statistics 2024-12-25 Badr Moufad , Yazid Janati , Lisa Bedin , Alain Durmus , Randal Douc , Eric Moulines , Jimmy Olsson

Masked diffusion models (MDMs) have recently emerged as a novel framework for language modeling. MDMs generate sentences by iteratively denoising masked sequences, filling in [MASK] tokens step by step. Although MDMs support any-order…

Machine Learning · Computer Science 2026-02-27 Chunsan Hong , Seonho An , Min-Soo Kim , Jong Chul Ye

For over 30 years, mode-coupling theory (MCT) has been the de facto theoretic description of dense fluids and the liquid-glass transition. MCT, however, is limited by its ad hoc construction and lacks a mechanism to institute corrections.…

Soft Condensed Matter · Physics 2015-08-12 David D. McCowan

We study a coupled thermo-diffusion system that accounts for the dynamics of hot colloids in periodically heterogeneous media. Our model describes the joint evolution of temperature and colloidal concentrations in a saturated porous…

Analysis of PDEs · Mathematics 2017-04-07 Vo Anh Khoa , Adrian Muntean

Sampling from log-concave distributions is a well researched problem that has many applications in statistics and machine learning. We study the distributions of the form $p^{*}\propto\exp(-f(x))$, where…

Machine Learning · Computer Science 2019-09-13 Ruoqi Shen , Yin Tat Lee

We propose an approach to approximate the boundary crossing probabilities for general one-dimensional diffusion processes, and derive the convergence rate for this approximation scheme. There results are based on the explicit expression of…

Probability · Mathematics 2015-10-28 Jinghai Shao , Liqun Wang

We prove the hydrodynamic limit for the symmetric exclusion process with long jumps given by a mean zero probability transition rate with infinite variance and in contact with infinitely many reservoirs with density $\alpha$ at the left of…

Mathematical Physics · Physics 2018-03-05 Cedric Bernardin , Patricia Gonçalves , Byron Oviedo

We introduce a parametric family of models to characterize the properties of astrophysical systems in a quasi-stationary evolution under the incidence evaporation. We start from an one-particle distribution…

Astrophysics of Galaxies · Physics 2016-07-14 Y. J. Gomez-Leyton , L. Velazquez

For a wide class of continuous-time Markov processes, including all irreducible hypoelliptic diffusions evolving on an open, connected subset of $\RL^d$, the following are shown to be equivalent: (i) The process satisfies (a slightly weaker…

Probability · Mathematics 2016-04-27 Ioannis Kontoyiannis , Sean P. Meyn

In this paper, we derive results about the limiting distribution of the empirical magnetization vector and the maximum likelihood (ML) estimates of the natural parameters in the tensor Curie-Weiss Potts model. Our results reveal…

Statistics Theory · Mathematics 2023-07-25 Sanchayan Bhowal , Somabha Mukherjee

The term \emph{moderate deviations} is often used in the literature to mean a class of large deviation principles that, in some sense, fill the gap between a convergence in probability to zero (governed by a large deviation principle) and a…

Probability · Mathematics 2022-07-15 Rita Giuliano , Claudio Macci

We study parametric inference for ergodic diffusion processes with a degenerate diffusion matrix. Existing research focuses on a particular class of hypo-elliptic SDEs, with components split into `rough'/`smooth' and noise from rough…

Statistics Theory · Mathematics 2024-05-29 Yuga Iguchi , Alexandros Beskos , Matthew Graham

Laplace transforms for integrals of stochastic processes have been known in analytically closed form for just a handful of Markov processes: namely, the Ornstein-Uhlenbeck, the Cox-Ingerssol-Ross (CIR) process and the exponential of…

Probability · Mathematics 2007-10-09 Claudio Albanese , Stephan Lawi

We prove, for any $\beta >0$, a central limit theorem for the fluctuations of linear statistics in the Sine-$\beta$ process, which is the infinite volume limit of the random microscopic behavior in the bulk of one-dimensional log-gases at…

Probability · Mathematics 2018-09-11 Thomas Leblé

Evaporating droplets and films are used in applications from different fields. Various methods of evaporative self-assembly are of particular interest. The paper describes a mathematical model of mass transfer in a droplet drying on a…

Fluid Dynamics · Physics 2023-09-22 Konstantin S. Kolegov

We address the numerical treatment of source terms in algebraic flux correction schemes for steady convection-diffusion-reaction (CDR) equations. The proposed algorithm constrains a continuous piecewise-linear finite element approximation…

Numerical Analysis · Mathematics 2024-01-09 Petr Knobloch , Dmitri Kuzmin , Abhinav Jha

The Pearson family of ergodic diffusions with a quadratic diffusion coefficient and a linear force are characterized by explicit dynamics of their integer moments and by explicit relaxation spectral properties towards their steady state.…

Statistical Mechanics · Physics 2023-08-14 Cecile Monthus

By using the spectrum of the underlying symmetric diffusion operator, the convergence in $L^p$-Wasserstein distance $\mathbb W_p (p\ge 1)$ is characterized for the empirical measure $\mu_t$ of non-symmetric subordinated diffusion processes…

Probability · Mathematics 2023-02-28 Feng-Yu Wang
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