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The diffusion model has shown success in generating high-quality and diverse solutions to trajectory optimization problems. However, diffusion models with neural networks inevitably make prediction errors, which leads to constraint…

Machine Learning · Computer Science 2024-06-04 Anjian Li , Zihan Ding , Adji Bousso Dieng , Ryne Beeson

Transient diffusion equations arise in many branches of engineering and applied sciences (e.g., heat transfer and mass transfer), and are parabolic partial differential equations. It is well-known that, under certain assumptions on the…

Numerical Analysis · Computer Science 2013-08-06 K. B. Nakshatrala , H. Nagarajan , M. Shabouei

Real-world data generation often involves complex inter-dependencies among instances, violating the IID-data hypothesis of standard learning paradigms and posing a challenge for uncovering the geometric structures for learning desired…

Machine Learning · Computer Science 2023-05-30 Qitian Wu , Chenxiao Yang , Wentao Zhao , Yixuan He , David Wipf , Junchi Yan

We derive thermodynamically consistent models of reaction-diffusion equations coupled to a heat equation. While the total energy is conserved, the total entropy serves as a driving functional such that the full coupled system is a gradient…

Analysis of PDEs · Mathematics 2018-10-16 Jan Haskovec , Sabine Hittmeir , Peter Markowich , Alexander Mielke

A comprehensive methodology for establishing the existence of gradient flows for cross-diffusion systems with respect to suitable energies is proposed. The approach is based on the construction of piecewise-in-time constant approximations…

Analysis of PDEs · Mathematics 2026-04-03 Mathias Dus , Ansgar Jüngel

We establish weak-strong uniqueness and stability properties of renormalised solutions to a class of energy-reaction-diffusion systems. The systems considered are motivated by thermodynamically consistent models, and their formal entropy…

Analysis of PDEs · Mathematics 2022-05-03 Katharina Hopf

Generative models such as denoising diffusion models are quickly advancing their ability to approximate highly complex data distributions. They are also increasingly leveraged in scientific machine learning, where samples from the implied…

Machine Learning · Computer Science 2025-03-14 Jan-Hendrik Bastek , WaiChing Sun , Dennis M. Kochmann

The global-in-time existence of renormalized solutions to reaction-cross-diffu-sion systems for an arbitrary number of variables in bounded domains with no-flux boundary conditions is proved. The cross-diffusion part describes the…

Analysis of PDEs · Mathematics 2017-11-07 Xiuqing Chen , Ansgar Jüngel

We introduce a simple model of the time evolution of a binary mixture of compressible fluids including the thermal effects. Despite its apparent simplicity, the model is thermodynamically consistent admitting an entropy balance equation. We…

Analysis of PDEs · Mathematics 2021-09-07 Eduard Feireisl , Madalina Petcu , Bangwei She

A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution, is presented. No knowledge beyond the support of the…

Information Theory · Computer Science 2007-07-13 Joseph DeStefano , Erik Learned-Miller

In this paper we analyse a class of nonlinear cross-diffusion systems for two species with local repulsive interactions that exhibit a formal gradient flow structure with respect to the Wasserstein metric. We show that systems where the…

Analysis of PDEs · Mathematics 2019-06-11 M. Burger , J. A. Carrillo , J. -F. Pietschmann , M. Schmidtchen

The paper presents a versatile framework for solids which undergo nonisothermal processes with irreversibly changing microstructure at large strains. It outlines rate-type and incremental variational principles for the full thermomechanical…

Numerical Analysis · Mathematics 2022-04-12 Stephan Teichtmeister , Marc-Andre Keip

A model for diffusion on a cubic lattice with a random distribution of traps is developed. The traps are redistributed at certain time intervals. Such models are useful for describing systems showing dynamic disorder, such as ion-conducting…

Condensed Matter · Physics 2009-10-31 S. Mandal , R. Dasgupta

We consider a system of random walks in a random environment interacting via exclusion. The model is reversible with respect to a family of disordered Bernoulli measures. Assuming some weak mixing conditions, it is shown that, under…

Probability · Mathematics 2007-05-23 Jeremy Quastel

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…

The self-diffusion process of a hard sphere fluid confined by two parallel plates separated by a distance on the order of the particle diameter is studied. The starting point is a closed kinetic equation for the distribution function that…

Statistical Mechanics · Physics 2025-10-24 Manuel Mayo , María Isabel García de Soria , Pablo Maynar , José Javier Brey

In this paper we propose and validate a multiscale model for the description of particle diffusion in presence of trapping boundaries. We start from a drift-diffusion equation in which the drift term describes the effect of bubble traps,…

Numerical Analysis · Mathematics 2023-07-11 Clarissa Astuto , Antonio Raudino , Giovanni Russo

By generalizing a class of models recently introduced to account for protracted transients in biological systems, we identify a novel mechanism for hyperuniformity. In this model, competition of particles over a shared resource guides the…

Statistical Mechanics · Physics 2025-12-11 Tal Agranov , Natan Wiegenfeld , Omer Karin , Benjamin D. Simons

A hyperbolic system approach is proposed for robust computation of anisotropic diffusion equations that appear in quasineutral plasmas. Though the approach exhibits merits of high extensibility and accurate flux computation, the…

Numerical Analysis · Mathematics 2025-09-12 Tokuhiro Eto , Rei Kawashima

The superposition principle is fundamental to linear wave systems, ensuring that their physical behaviour is independent of the chosen basis representation. While this principle underpins many analytical techniques, including modal…

Classical Physics · Physics 2026-03-26 Michael Mazilu , Andriejus Demčenko