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In this paper we consider the Dirichlet form on the half-space $\mathbb{R}^d_+$ defined by the jump kernel $J(x,y)=|x-y|^{-d-\alpha}\mathcal{B}(x,y)$, where $\mathcal{B}(x,y)$ can be degenerate at the boundary. Unlike our previous works…

Probability · Mathematics 2022-12-06 Panki Kim , Renming Song , Zoran Vondraček

This paper introduces Discrete Markov Probabilistic Models (DMPMs), a novel discrete diffusion algorithm for discrete data generation. The algorithm operates in discrete bit space, where the noising process is a continuous-time Markov chain…

Machine Learning · Statistics 2025-10-09 Le-Tuyet-Nhi Pham , Dario Shariatian , Antonio Ocello , Giovanni Conforti , Alain Durmus

This paper is devoted to a fractional generalization of the Dirichlet distribution. The form of the multivariate distribution is derived assuming that the $n$ partitions of the interval $[0,W_n]$ are independent and identically distributed…

Probability · Mathematics 2021-02-17 Elvira Di Nardo , Federico Polito , Enrico Scalas

A diffusion taking value in probability measures on a graph with a vertex set $V$, $\sum_{i\in V}x_i\delta_i$, is studied. The masses on each vertices satisfy the stochastic differential equation of the form $dx_i=\sum_{j\in…

Probability · Mathematics 2023-03-13 Shuhei Mano

A correlated random walk approach to diffusion is applied to the disordered nonoverlapping Lorentz gas. By invoking the Lu-Torquato theory for chord-length distributions in random media [J. Chem. Phys. 98, 6472 (1993)], an analytic…

Statistical Mechanics · Physics 2008-02-16 Artur B. Adib

In [10], a `Markovian stick-breaking' process which generalizes the Dirichlet process $(\mu, \theta)$ with respect to a discrete base space ${\mathfrak X}$ was introduced. In particular, a sample from from the `Markovian stick-breaking'…

Statistics Theory · Mathematics 2021-08-25 William Lippitt , Sunder Sethuraman

We reconsider the problem of diffusion of particles at constant speed and present a generalization of the Telegrapher process to higher dimensional stochastic media ($d>1$), where the particle can move along $2^d$ directions. We derive the…

Disordered Systems and Neural Networks · Physics 2009-10-31 S. Anantha Ramakrishna , N. Kumar

A general formulation of translationally invariant, parametrically correlated random matrix ensembles, is used to classify universality in correlation functions. Surprisingly, the range of possible physical systems is bounded, and can be…

chao-dyn · Physics 2016-08-31 Dimitri Kusnezov , Caio H. Lewenkopf

We present a stable characterization of on-diagonal upper bounds for heat kernels associated with regular Dirichlet forms on metric measure spaces satisfying the volume doubling property. Our conditions include integral bounds on the jump…

Analysis of PDEs · Mathematics 2025-01-14 Soobin Cho

In this paper, we consider a symmetric pure jump Markov process $X$ on a metric measure space with volume doubling conditions. Our focus is on estimating the transition density $p(t,x,y)$ of $X$ and studying its stability when the jumping…

Probability · Mathematics 2023-06-05 Joohak Bae , Jaehoon Kang , Panki Kim , Jaehun Lee

We exploit dynamical properties of diagonal actions to derive results in Diophantine approximations. In particular, we prove that the continued fraction expansion of almost any point on the middle third Cantor set (with respect to the…

Dynamical Systems · Mathematics 2011-01-21 Manfred Einsiedler , Lior Fishman , Uri Shapira

Let $X=(X_1,X_2,\ldots)$ be a sequence of random variables with values in a standard space $(S,\mathcal{B})$. Suppose \begin{gather*} X_1\sim\nu\quad\text{and}\quad P\bigl(X_{n+1}\in\cdot\mid…

Probability · Mathematics 2022-04-05 Patrizia Berti , Emanuela Dreassi , Fabrizio Leisen , Luca Pratelli , Pietro Rigo

Self-interacting diffusions are processes living on a compact Riemannian manifold defined by a stochastic differential equation with a drift term depending on the past empirical measure of the process. The asymptotics of this measure is…

Probability · Mathematics 2009-08-03 Michel Benaim , Olivier Raimond

Stick-breaking has a long history and is one of the most popular procedures for constructing random discrete distributions in Statistics and Machine Learning. In particular, due to their intuitive construction and computational tractability…

Statistics Theory · Mathematics 2026-01-26 María F. Gil-Leyva , Antonio Lijoi , Ramsés H. Mena , Igor Prünster

This work provides an extension of parts of the classical finite dimensional sub-elliptic theory in the context of infinite dimensional compact connected metrizable groups. Given a well understood and well behaved bi-invariant Laplacian,…

Probability · Mathematics 2025-03-03 Qi Hou , Laurent Saloff-Coste

Score-based diffusion models have demonstrated outstanding empirical performance in machine learning and artificial intelligence, particularly in generating high-quality new samples from complex probability distributions. Improving the…

Machine Learning · Statistics 2025-05-30 Yuchen Jiao , Gen Li

This paper improves a previously established test involving only coefficients to decide a priori whether or not non-trivial symmetries of a large class of space-time dependent diffusion processes on the real line exist. When the existence…

Mathematical Physics · Physics 2024-04-19 F. Güngör

We revisit the diffusion properties and the mean drift induced by an external field of a random walk process in a class of branched structures, as the comb lattice and the linear chains of plaquettes. A simple treatment based on scaling…

Statistical Mechanics · Physics 2013-11-21 Giuseppe Forte , Raffaella Burioni , Fabio Cecconi , Angelo Vulpiani

Let $\alpha$ be a Steinhaus random multiplicative function. For a wide class of multiplicative functions $f$ we construct a multiplicative chaos measure arising from the Dirichlet series of $\alpha f$, in the whole $L^1$-regime. Our method…

Number Theory · Mathematics 2025-09-16 Ofir Gorodetsky , Mo Dick Wong

The mean square displacement per collision of a molecule immersed in a gas at equilibrium is given by its mean square displacement between two consecutive collisions (mean square free path) corrected by a prefactor in the form of a series.…

Soft Condensed Matter · Physics 2024-07-03 Santos Bravo Yuste , Rubén Gómez González , Vicente Garzó
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