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Diffusion and flow-based generative models have achieved remarkable success in domains such as image synthesis, video generation, and natural language modeling. In this work, we extend these advances to weight space learning by leveraging…

Machine Learning · Computer Science 2025-10-17 Daniel Saragih , Deyu Cao , Tejas Balaji

Geometrical random multiplicative cascade processes are often used to model positive-valued multifractal fields such as the energy dissipation in fully developed turbulence. We propose a dynamical generalization describing the energy…

Condensed Matter · Physics 2015-06-24 Juergen Schmiegel , Jochen Cleve , Hans C. Eggers , Bruce R. Pearson , Martin Greiner

For scalar reaction-diffusion in one space dimension, it is known for a long time that fronts move with an exponentially small speed for potentials with several distinct mini- mizers. The purpose of this paper is to provide a similar result…

Analysis of PDEs · Mathematics 2009-10-09 Fabrice Bethuel , Didier Smets , Giandomenico Orlandi

We study the convergence of stochastic time-discretization schemes for evolution equations driven by random velocity fields, including examples like stochastic gradient descent and interacting particle systems. Using a unified framework…

Functional Analysis · Mathematics 2025-05-28 Giulia Cavagnari , Giuseppe Savaré , Giacomo Enrico Sodini

Gradient-based learning in multi-layer neural networks displays a number of striking features. In particular, the decrease rate of empirical risk is non-monotone even after averaging over large batches. Long plateaus in which one observes…

Machine Learning · Computer Science 2025-03-25 Raphaël Berthier , Andrea Montanari , Kangjie Zhou

We address the question of global in time existence of solutions to a magnetoviscoelastic system with general initial data. We show that the notion of dissipative solutions allows to prove such an existence in two and three dimensions. This…

Analysis of PDEs · Mathematics 2019-12-23 Martin Kalousek , Anja Schlömerkemper

Stability landscapes are useful for understanding the properties of dynamical systems. These landscapes can be calculated from the system's dynamical equations using the physical concept of scalar potential. Unfortunately, for most…

Quantitative Methods · Quantitative Biology 2020-04-24 Pablo Rodríguez-Sánchez , Egbert H. van Nes , Marten Scheffer

A fully coupled system of two second-order parabolic degenerate equations arising as a thin film approximation to the Muskat problem is interpreted as a gradient flow for the 2-Wasserstein distance in the space of probability measures with…

Analysis of PDEs · Mathematics 2013-08-29 Philippe Laurencot , Bogdan-Vasile Matioc

Gradient-based methods are widely used to solve various optimization problems, however, they are either constrained by local optima dilemmas, simple convex constraints, and continuous differentiability requirements, or limited to…

Machine Learning · Computer Science 2026-03-19 Ming Li

Given a one-dimensional stochastic differential equation, one can associate to this equation a stochastic flow on $[0,+\infty )$, which has an absorbing barrier at zero. Then one can define its dual stochastic flow. In \cite{AW}, Akahori…

Probability · Mathematics 2015-09-01 Takafumi Amaba , Dai Taguchi , Go Yuki

This paper develops the so-called Weighted Energy-Dissipation (WED) variational approach for the analysis of gradient flows in metric spaces. This focuses on the minimization of the parameter-dependent global-in-time functional of…

Analysis of PDEs · Mathematics 2018-01-17 Riccarda Rossi , Giuseppe Savaré , Antonio Segatti , Ulisse Stefanelli

By viewing a velocity gradient in a fluid as an internal disturbance and treating it as a constraint on the wave function of a system, a linear evolution equation for the wave function is obtained from the Lagrange multiplier method. It…

Statistical Mechanics · Physics 2012-11-13 M. -L. Zhang , D. A. Drabold

This thesis analyze the Wasserstein gradient flow of a functional defined as a double convolution of a non-smooth repulsive interaction potential. To be more precise, the potential under investigation has a -|x| behavior close to the…

Analysis of PDEs · Mathematics 2013-10-15 Giovanni A. Bonaschi

The energy dissipation law and the maximum bound principle (MBP) are two important physical features of the well-known Allen-Cahn equation. While some commonly-used first-order time stepping schemes have turned out to preserve…

Numerical Analysis · Mathematics 2022-03-10 Lili Ju , Xiao Li , Zhonghua Qiao

We consider the gradient flow of a one-homogeneous functional, whose dual involves the derivative of a constrained scalar function. We show in this case that the gradient flow is related to a weak, generalized formulation of the Hele-Shaw…

Analysis of PDEs · Mathematics 2012-03-09 Ariela Briani , Antonin Chambolle , Matteo Novaga , Giandomenico Orlandi

We develop a model in two dimensions to characterise the growth rate of a tracer gradient mixed by a statistically homogeneous flow with rapid temporal variations. % % The model is based on the orientation dynamics of the passive-tracer…

Fluid Dynamics · Physics 2010-05-05 Lennon Ó Náraigh

A framework is presented to design multirate time stepping algorithms for two dissipative models with coupling across a physical interface. The coupling takes the form of boundary conditions imposed on the interface, relating the solution…

Numerical Analysis · Mathematics 2021-12-14 Jeffrey M. Connors , K. Chad Sockwell

An implicit variable-step BDF2 scheme is established for solving the space fractional Cahn-Hilliard equation, involving the fractional Laplacian, derived from a gradient flow in the negative order Sobolev space $H^{-\alpha}$,…

Numerical Analysis · Mathematics 2023-06-26 Xuan Zhao , Zhongqin Xue

We study the evolution of closed inextensible planar curves under a second order flow that decreases the $p$-elastic energy. A short time existence result for $p \in (1,\infty)$ is obtained via a minimizing movements method. For $p = 2$,…

Differential Geometry · Mathematics 2018-11-19 Shinya Okabe , Paola Pozzi , Glen Wheeler

This paper proposes a data-driven learning framework for identifying governing laws of generalized diffusions with non-gradient components. By combining energy dissipation laws with a physically consistent penalty and first-moment…

Computational Physics · Physics 2025-08-11 Fanze Kong , Chen-Chih Lai , Yubin Lu