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Diffusion models have emerged as one of the most promising frameworks for deep generative modeling. In this work, we explore the potential of non-uniform diffusion models. We show that non-uniform diffusion leads to multi-scale diffusion…

Machine Learning · Computer Science 2022-07-21 Georgios Batzolis , Jan Stanczuk , Carola-Bibiane Schönlieb , Christian Etmann

Simulation of conditioned diffusion processes is an essential tool in inference for stochastic processes, data imputation, generative modelling, and geometric statistics. Whilst simulating diffusion bridge processes is already difficult on…

Probability · Mathematics 2024-04-24 Erlend Grong , Karen Habermann , Stefan Sommer

We present a new method of deriving a boundary condition at a thin membrane for diffusion from experimental data. Based on experimental results obtained for normal diffusion of ethanol in water, we show that the derived boundary condition…

Statistical Mechanics · Physics 2017-07-12 Tadeusz Kosztołowicz , Sławomir Wąsik , Katarzyna D. Lewandowska

Light diffusion is usually associated with thick, opaque media. Indeed, multiple scattering is necessary for the onset of the diffusive regime and such condition is generally not met in almost transparent media. Nonetheless, at long enough…

A detailed description and validation of a recently developed integration scheme is here reported for one- and two-dimensional reaction-diffusion models. As paradigmatic examples of this class of partial differential equations the complex…

Statistical Mechanics · Physics 2015-06-25 M. Nitti , A. Torcini , S. Ruffo

Generative diffusion models are extensively used in unsupervised and self-supervised machine learning with the aim to generate new samples from a probability distribution estimated with a set of known samples. They have demonstrated…

Fluid Dynamics · Physics 2026-01-28 Wilfried Genuist , Éric Savin , Filippo Gatti , Didier Clouteau

The process referred to as "semi-convection" in astrophysics and "double-diffusive convection in the diffusive regime" in Earth and planetary sciences, occurs in stellar and planetary interiors in regions which are stable according to the…

Solar and Stellar Astrophysics · Physics 2015-06-03 Giovanni M. Mirouh , Pascale Garaud , Stephan Stellmach , Adrienne L. Traxler , Toby S. Wood

Semiconductor model is a system of parabolic partial differential equations with cross-diffusion phenomenon. Previous results showed that a weak solution exists and is not bounded in general. So semiconductor model was categorized as a…

Probability · Mathematics 2025-12-30 Xi Lin

While various phase-field models have recently appeared for two-phase fluids with different densities, only some are known to be thermodynamically consistent, and practical stable schemes for their numerical simulation are lacking. In this…

As a simplified model for subsurface flows elliptic equations may be utilized. Insufficient measurements or uncertainty in those are commonly modeled by a random coefficient, which then accounts for the uncertain permeability of a given…

Numerical Analysis · Mathematics 2019-02-07 Andrea Barth , Andreas Stein

A new solution to the mono-dimensional diffusion equation for time-variable first kind boundary condition is presented where the time-variable function at the surface is derived proposing a surface saturation model. This solution may be…

Materials Science · Physics 2022-12-08 Guglielmo Macrelli

Experiments on particles' motion in living cells show that it is often subdiffusive. This subdiffusion may be due to trapping, percolation-like structures, or viscoelatic behavior of the medium. While the models based on trapping (leading…

Disordered Systems and Neural Networks · Physics 2015-06-11 Yasmine Meroz , Igor M. Sokolov , Joseph Klafter

A recently introduced nonlinear Fokker-Planck equation, derived directly from a master equation, comes out as a very general tool to describe phenomenologically systems presenting complex behavior, like anomalous diffusion, in the presence…

Statistical Mechanics · Physics 2009-11-13 Veit Schwammle , Evaldo M. F. Curado , Fernando D. Nobre

We present the first diffusion-based framework that can learn an unknown distribution using only highly-corrupted samples. This problem arises in scientific applications where access to uncorrupted samples is impossible or expensive to…

Machine Learning · Computer Science 2023-05-31 Giannis Daras , Kulin Shah , Yuval Dagan , Aravind Gollakota , Alexandros G. Dimakis , Adam Klivans

We show existence and uniqueness of strong solutions to a Navier-Stokes/Cahn-Hilliard type system on a given two-dimensional evolving surface in the case of different densities and a singular (logarithmic) potential. The system describes a…

Analysis of PDEs · Mathematics 2024-08-15 Helmut Abels , Harald Garcke , Andrea Poiatti

We propose a new approach to simulate hypothetical physics processes which are defined by multiple free parameters. Compared to the conventional grid-scan approach, the new method can produce accurate estimations of the detector acceptance…

High Energy Physics - Experiment · Physics 2012-06-01 Jiahang Zhong , Run-Sheng Huang , Shih-Chang Lee

Nonlinear time fractional partial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. For solving these problems, one often uses coarse spatial grid…

Numerical Analysis · Mathematics 2022-07-13 Wenyuan Li , Anatoly Alikhanov , Yalchin Efendiev , Wing Tat Leung

In the present paper we propose a reduced temperature non-equilibrium model for simulating multicomponent flows with inter-phase heat transfer, diffusion processes (including the viscosity and the heat conduction) and external energy…

Numerical Analysis · Mathematics 2021-08-19 Chao Zhang , Lifeng Wang , Zhijun Shen , Zhiyuan Li , Igor Menshov

The aim of this paper is to study the behavior of the weighted empirical measures of the decreasing step Euler scheme of a one-dimensional diffusion process having multiple invariant measures. This situation can occur when the drift and the…

Probability · Mathematics 2018-02-20 Vincent Lemaire

Earth System Models (ESMs) are essential tools for understanding the impact of human actions on Earth's climate. One key application of these models is studying extreme weather events, such as heat waves or dry spells, which have…

Atmospheric and Oceanic Physics · Physics 2023-04-25 Seth Bassetti , Brian Hutchinson , Claudia Tebaldi , Ben Kravitz