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Related papers: Yaglom limit for Stochastic Fluid Models

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We develop a quantitative statistical theory of transformers in the large-context regime by adopting the abstraction of contextual flow maps (CFMs): dynamical systems that evolve a distinguished token in the presence of a contextual measure…

Machine Learning · Computer Science 2026-05-19 Shi Chen , Zhengjiang Lin , Kaizhao Liu , Philippe Rigollet

Standard flow matching scales well but typically relies on an unstructured source distribution, limiting its ability to learn interpretable latent structure. Latent-variable models, by contrast, capture structure but often sacrifice…

Machine Learning · Computer Science 2026-05-11 Xavier Sumba , Carles Balsells-Rodas , Yingzhen Li

In the supercritical fluid (SCF) region, at temperatures and pressures above the critical point, the thermodynamic singularity separating liquids and gases no longer exists. Recent arguments based on thermodynamics and critical scalings…

Statistical Mechanics · Physics 2026-01-23 Sha Jin , Xinyang Li , Xue Fan , Matteo Baggioli , Yuliang Jin

The general theory developed by Ben Yaacov for metric structures provides Fra\"iss\'e limits which are approximately ultrahomogeneous. We show here that this result can be strengthened in the case of relational metric structures. We give an…

Logic · Mathematics 2019-08-13 David Bryant , André Nies , Paul Tupper

Yield-stress is a problematic and controversial non-Newtonian flow phenomenon. In this article, we investigate the flow of yield-stress substances through porous media within the framework of pore-scale network modeling. We also investigate…

Fluid Dynamics · Physics 2010-05-12 Taha Sochi

We study the stochastic fractional diffusive limit of a kinetic equation involving a small parameter and perturbed by a smooth random term. Generalizing the method of perturbed test functions, under an appropriate scaling for the small…

Analysis of PDEs · Mathematics 2013-12-10 Sylvain De Moor

Yield-stress materials, which require a sufficiently large forcing to flow, are currently ill-understood theoretically. To gain insight into their yielding transition, here we study numerically the rheology of a suspension of deformable…

Currently, there is no general theory for deriving diffusion approximations of queueing systems with high- or infinite-dimensional state descriptors. In this paper, we explore one path for deriving diffusion limit equations of queueing…

Probability · Mathematics 2026-05-28 Eva H Loeser

This article is concerned with rigorously justifying the hydrostatic limit for continuously stratified incompressible fluids under the influence of gravity. The main distinction of this work compared to previous studies is the absence of…

Analysis of PDEs · Mathematics 2025-01-06 Vincent Duchêne , Roberta Bianchini

This work provides a novel convergence analysis for stochastic optimization in terms of stopping times, addressing the practical reality that algorithms are often terminated adaptively based on observed progress. Unlike prior approaches,…

Optimization and Control · Mathematics 2025-07-17 Yasong Feng , Yifan Jiang , Tianyu Wang , Zhiliang Ying

We study the flow of a Bingham yield-stress fluid in a pore network model where the throats have radii drawn from a uniform distribution. We consider the case in which a fraction of the largest radii is blocked. The fluid can flow only…

Fluid Dynamics · Physics 2026-03-18 Nathan Abitbol , Alex Hansen , Alberto Rosso , Laurent Talon

We derive a finite-sample probabilistic bound on the parameter estimation error of a system identification algorithm for Linear Switched Systems. The algorithm estimates Markov parameters from a single trajectory and applies a variant of…

Machine Learning · Computer Science 2025-05-19 Daniel Racz , Mihaly Petreczky , Balint Daroczy

In this paper, we study the limiting distribution of the eigenvalues for random tridiagonal matrix models. The limiting distribution is well described by its moments. Here, an analytical approach allows us, as in the case of Wigner…

Probability · Mathematics 2025-12-04 Lucas Babet , Ionel Popescu

We prove universality of the Yaglom limit of Lipschitz cones among all unimodal L\'{e}vy processes sufficiently close to the isotropic $\alpha$-stable L\'{e}vy process.

Probability · Mathematics 2021-10-05 Gavin Armstrong , Krzysztof Bogdan , Tomasz Grzywny , Łukasz Leżaj , Longmin Wang

Generative models excel at synthesizing high-fidelity samples from complex data distributions, but they often violate hard constraints arising from physical laws or task specifications. A common remedy is to project intermediate samples…

Machine Learning · Computer Science 2025-09-30 Jinhao Liang , Yixuan Sun , Anirban Samaddar , Sandeep Madireddy , Ferdinando Fioretto

An exact analytical solution of the statistical multifragmentation model is found in thermodynamic limit. Excluded volume effects are taken into account in the thermodynamically self-consistent way. The model exhibits a 1-st order phase…

Nuclear Theory · Physics 2007-05-23 K. A. Bugaev , M. I. Gorenstein , I. N. Mishustin , W. Greiner

A stochastic model for a mobile network is studied. Users enter the network, and then perform independent Markovian routes between nodes where they receive service according to the Processor-Sharing policy. Once their service requirement is…

Probability · Mathematics 2010-01-14 Florian Simatos , Danielle Tibi

The aim of this note is to state a couple of general results about the properties of the penalized maximum likelihood estimators (pMLE) and of the posterior distribution for parametric models in a non-asymptotic setup and for possibly large…

Statistics Theory · Mathematics 2022-12-13 Vladimir Spokoiny

Yield stress fluids (YSFs) display a dual nature highlighted by the existence of a yield stress such that YSFs are solid below the yield stress, whereas they flow like liquids above it. Under an applied shear rate $\dot\gamma$, the…

Flow Matching (FM) (also referred to as stochastic interpolants or rectified flows) stands out as a class of generative models that aims to bridge in finite time the target distribution $\nu^\star$ with an auxiliary distribution $\mu$,…

Machine Learning · Statistics 2024-09-16 Marta Gentiloni Silveri , Giovanni Conforti , Alain Durmus
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