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Diffusion models offer stable training and state-of-the-art performance for deep generative modeling tasks. Here, we consider their use in the context of multivariate subsurface modeling and probabilistic inversion. We first demonstrate…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Roberto Miele , Niklas Linde

Neutron diffraction, magnetization and muon spin relaxation measurements, supplemented by density functional theory (DFT) calculations are employed to unravel temperature-driven magnetization reversal (MR) in inverse spinel Co$_2$VO$_4$.…

We have studied the conductance distribution function of two-dimensional disordered noninteracting systems in the crossover regime between the diffusive and the localized phases. The distribution is entirely determined by the mean…

Disordered Systems and Neural Networks · Physics 2015-05-14 A. M. Somoza , J. Prior , M. Ortuno , I. V. Lerner

We show that truncated rotating square waveguide arrays support new types of localized modes that exist even in the linear case, in complete contrast to localized excitations in nonrotating arrays requiring nonlinearity for their existence…

Signaling molecules play an important role for many cellular functions. We investigate here a general system of two membrane reaction-diffusion equations coupled to a diffusion equation inside the cell by a Robin-type boundary condition and…

Analysis of PDEs · Mathematics 2015-06-16 Andreas Rätz , Matthias Röger

We investigate what kind of images lie in the high-density regions of diffusion models. We introduce a theoretical mode-tracking process capable of pinpointing the exact mode of the denoising distribution, and we propose a practical…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Rafał Karczewski , Markus Heinonen , Vikas Garg

Diffusion exchange spectroscopy (DEXSY) is a method to probe exchange between domains of varying confinement. Analyses of DEXSY signals typically assume Gaussian diffusion within distinct compartments and first-order exchange kinetics…

Materials Science · Physics 2026-03-31 Teddy X Cai , Nathan H Williamson , Peter J Basser

Probing the transport of fluids within confined domains is important in many areas including material science, catalysis, food science, and cell biology. The diffusion propagator fully characterizes the diffusion process, which is highly…

Problems with localized nonhomogeneous material properties present well-known challenges for numerical simulations. In particular, such problems may feature large differences in length scales, causing difficulties with meshing and…

Numerical Analysis · Mathematics 2021-11-23 Alex Viguerie , Silvia Bertoluzza , Alessandro Veneziani , Ferdinando Auricchio

Localized deformation patterns are a common motif in morphogenesis and are increasingly finding widespread applications in materials science, for instance as memory devices. Here we describe the emergence of spatially localized deformations…

Soft Condensed Matter · Physics 2019-06-12 Thomas C. T. Michaels , Remy Kusters , Alexander J. Dear , Cornelis Storm , James C. Weaver , L. Mahadevan

Diffusion models have shown remarkable empirical success in sampling from rich multi-modal distributions. Their inference relies on numerically solving a certain differential equation. This differential equation cannot be solved in closed…

Machine Learning · Computer Science 2026-01-16 Khashayar Gatmiry , Sitan Chen , Adil Salim

Demixing of binary fluids subjected to slow temperature ramps shows repeated waves of nucleation which arise as a consequence of the competition between generation of supersaturation by the temperature ramp and relaxation of supersaturation…

Statistical Mechanics · Physics 2012-10-16 Izabella J. Benczik , Jürgen Vollmer

The aim of this paper is to provide a comprehensive study of some linear nonlocal diffusion problems in metric measure spaces. These include, for example, open subsets in $\mathbb{R}^N$, graphs, manifolds, multi-structures or some fractal…

Analysis of PDEs · Mathematics 2014-12-18 Aníbal Rodríguez-Bernal , Silvia Sastre-Gómez

In this paper, we study the localization phenomena in a slender cylinder composed of an incompressible hyperelastic material subjected to axial tension. We aim to construct the analytical solutions based on a three-dimensional setting and…

Classical Physics · Physics 2007-11-20 Huihui Dai , Yanhong Hao , Zhen Chen

We have studied the reflection delay time distribution from a one-dimensional electronically random system of finite length. We show that the average delay time is a non-monotonic function of the strength of the disorder and exhibits three…

Disordered Systems and Neural Networks · Physics 2009-10-31 Sandeep K. Joshi , A. M. Jayannavar

Brownian diffusion of rod-like polymers in the presence of randomly distributed spherical obstacles is studied using molecular dynamics (MD) simulations. It is observed that dependence of the reduced diffusion coefficient of these…

Soft Condensed Matter · Physics 2015-05-20 Farzaneh Sakha , Hossein Fazli

Localization and delocalization of quantum diffusion in time-continuous one-dimensional Anderson model perturbed by the quasi-periodic harmonic oscillations of $M$ colors is investigated systematically, which has been partly reported by the…

Disordered Systems and Neural Networks · Physics 2022-05-11 Hiroaki S. Yamada , Kensuke S. Ikeda

Diffusion, a fundamental internal mechanism emerging in many physical processes, describes the interaction among different objects. In many learning tasks with limited training samples, the diffusion connects the labeled and unlabeled data…

Machine Learning · Computer Science 2023-05-02 Tangjun Wang , Zehao Dou , Chenglong Bao , Zuoqiang Shi

Models of many-body localization (MBL) exhibit slow numerical drifts towards delocalization with increasing system size, for which no satisfactory theory exists. Numerics indicates that these drifts are driven by the proliferation of…

Disordered Systems and Neural Networks · Physics 2026-05-08 Carlo Vanoni , David M. Long , Anushya Chandran

Diffusion models have found valuable applications in anomaly detection by capturing the nominal data distribution and identifying anomalies via reconstruction. Despite their merits, they struggle to localize anomalies of varying scales,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Justin Tebbe , Jawad Tayyub