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Related papers: A note on Fokker-Planck equations and graphons

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An $L^2(R^d)$-valued stochastic N-interacting particle systems is investigated. Existence and uniqueness of solutions for the degenerate nonlinear Fokker-Planck equation for probability measures that corresponds to the mean field limit…

Probability · Mathematics 2023-10-16 Xueru Liu , Xuan Yang , Wei Wang

This paper deals with the derivation of the mean-field limit for multi-agent systems on a large class of sparse graphs. More specifically, the case of non-exchangeable multi-agent systems consisting of non-identical agents is addressed. The…

Probability · Mathematics 2025-11-21 Pierre-Emmanuel Jabin , David Poyato , Juan Soler

Recently, the theory of dense graph limits has received attention from multiple disciplines including graph theory, computer science, statistical physics, probability, statistics, and group theory. In this paper we initiate the study of the…

Combinatorics · Mathematics 2015-03-09 Peter Diao , Dominique Guillot , Apoorva Khare , Bala Rajaratnam

We consider systems of interacting particles which are described by a second order Langevin equation. The class of equations considered includes the situation where the particle evolution is governed by Hamiltonian dynamics with additional…

Analysis of PDEs · Mathematics 2025-07-29 Fenna Müller , Max von Renesse , Johannes Zimmer

The recent theory of graph limits gives a powerful framework for understanding the properties of suitable (convergent) sequences $(G_n)$ of graphs in terms of a limiting object which may be represented by a symmetric function $W$ on…

Combinatorics · Mathematics 2012-08-21 Bela Bollobas , Svante Janson , Oliver Riordan

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

The derivation of effective descriptions for interacting many-body systems is an important branch of applied mathematics. We prove a propagation of chaos result for a system of $N$ particles subject to Newtonian time evolution with or…

Mathematical Physics · Physics 2025-05-20 Li Chen , Jinwook Jung , Peter Pickl , Zhenfu Wang

In many network problems, graphs may change by the addition of nodes, or the same problem may need to be solved in multiple similar graphs. This generates inefficiency, as analyses and systems that are not transferable have to be…

Signal Processing · Electrical Eng. & Systems 2019-11-11 Luana Ruiz , Luiz F. O. Chamon , Alejandro Ribeiro

We establish a quantitfied overdamped limit for kinetic Vlasov-Fokker-Planck equations with nonlocal interaction forces. We provide explicit bounds on the error between solutions of that kinetic equation and the limiting equation, which is…

Analysis of PDEs · Mathematics 2021-06-01 Young-Pil Choi , Oliver Tse

Natural physical, chemical, and biological dynamical systems are often complex, with heterogeneous components interacting in diverse ways. We show how simple graph neural networks can be designed to jointly learn the interaction rules and…

In this paper we proceed with investigation of connections between Fokker - Planck equation and continuum mechanics. We base upon expressions from our work [2], based upon the spectral decomposition of Fokker - Planck equation solution. In…

Chaotic Dynamics · Physics 2007-09-17 Igor A. Tanski

A stochastic treatment yielding to the derivation of a general Fokker-Planck equation is presented to model the slow convergence towards equilibrium of mean-field systems due to finite-N effects. The thermalization process involves notably…

Mathematical Physics · Physics 2011-09-28 W. Ettoumi , M. -C. Firpo

The Becker-D\"oring equations are an infinite dimensional system of ordinary differntial equations describing coagulation/fragmentation processes of species of integer sizes. Formal Taylor expansions motivate that its solution should be…

Classical Analysis and ODEs · Mathematics 2019-02-22 Gabriel Stoltz , Pierre Terrier

We consider three classes of linear non-symmetric Fokker-Planck equations having a unique steady state and establish exponential convergence of solutions towards the steady state with explicit (estimates of) decay rates. First,…

Analysis of PDEs · Mathematics 2023-08-21 Franz Achleitner , Anton Arnold , Dominik Stürzer

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the…

Machine Learning · Computer Science 2022-10-25 Zhichao Han , David S. Kammer , Olga Fink

We study a random model of deep multi-head self-attention in which the weights are resampled independently across layers and heads, as at initialization of training. Viewing depth as a time variable, the residual stream defines a…

Probability · Mathematics 2026-04-03 Hugo Koubbi , Borjan Geshkovski , Philippe Rigollet

We consider weakly interacting diffusions on time varying random graphs. The system consists of a large number of nodes in which the state of each node is governed by a diffusion process that is influenced by the neighboring nodes. The…

Probability · Mathematics 2017-02-16 Shankar Bhamidi , Amarjit Budhiraja , Ruoyu Wu

In this paper we continue the study of the derivation of different types of kinetic equations which arise from scaling limits of interacting particle systems. We began this study in \cite{NVW}. More precisely, we consider the derivation of…

Mathematical Physics · Physics 2021-03-18 Alessia Nota , Juan J. L. Velázquez , Raphael Winter

High-energy, multi-component plasmas in which pair creation and annihilation, lepton-lepton scattering, lepton-proton scattering, and Comptonization all contribute to establishing the particle and photon distributions, are present in a…

Astrophysics · Physics 2014-10-13 Sergei Nayakshin , Fulvio Melia

Graph neural networks (GNNs) are designed to process data associated with graphs. They are finding an increasing range of applications; however, as with other modern machine learning techniques, their theoretical understanding is limited.…

Disordered Systems and Neural Networks · Physics 2026-02-23 O. Duranthon , L. Zdeborová