Cover Image

Transport based particle methods for the Fokker-Planck-Landau equation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ilin, Vasily, Hu, Jingwei, Wang, Zhenfu
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis Machine Learning Analysis of PDEs 35Q84, 65M75, 49Q22, 68T07
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Neural Pushforward Samplers for Distributions from Fokker-Planck Equations by Weak Adversarial Training
by: He, Andrew Qing, et al.
Published: (2025)

Fully discrete energy-dissipative and conservative discrete gradient particle methods for a class of continuity equations
by: Hu, Jingwei, et al.
Published: (2024)

Weak Adversarial Neural Pushforward Method for the McKean-Vlasov / Mean-Field Fokker-Planck Equation
by: He, Andrew Qing, et al.
Published: (2026)

Neural Pushforward Samplers for the Fokker-Planck Equation on Embedded Riemannian Manifolds
by: He, Andrew Qing, et al.
Published: (2026)

Adaptive Probability Flow Residual Minimization for High-Dimensional Fokker-Planck Equations
by: Wu, Xiaolong, et al.
Published: (2025)

Stability of the spatially homogeneous Landau equation in relative entropy and applications to score-based numerical methods
by: Ilin, Vasily
Published: (2025)

Numerical stationary states for nonlocal Fokker-Planck equations via fixed points of consistency maps
by: Carrillo, José A., et al.
Published: (2026)

A supervised learning scheme for computing Hamilton-Jacobi equation via density coupling
by: Cui, Jianbo, et al.
Published: (2024)

Score-based deterministic density sampling
by: Ilin, Vasily, et al.
Published: (2025)

Variational structures for the Fokker--Planck equation with general Dirichlet boundary conditions
by: Quattrocchi, Filippo
Published: (2024)

A separable and asymptotic-preserving dynamical low-rank method for the Vlasov-Poisson-Fokker-Planck system
by: Zhang, Shiheng, et al.
Published: (2026)

Radon--Wasserstein Gradient Flows for Interacting-Particle Sampling in High Dimensions
by: Hess-Childs, Elias, et al.
Published: (2026)

The Collisional Particle-In-Cell Method for the Vlasov-Maxwell-Landau Equations
by: Bailo, Rafael, et al.
Published: (2024)

Training-Induced Escape from Token Clustering in a Mean-Field Formulation of Transformers
by: Isobe, Noboru, et al.
Published: (2026)

A variational perspective on the dissipative Hamiltonian structure of the Vlasov-Fokker-Planck equation
by: Park, Sangmin
Published: (2024)

On a Vlasov-Fokker-Planck equation for stored electron beams
by: Cesbron, Ludovic, et al.
Published: (2023)

Well-posedness of the Fractional Fokker-Planck Equation
by: Chen, Ke, et al.
Published: (2025)

Resolvent approaches to elliptic regularity in stationary Fokker-Planck equations
by: Lee, Haesung
Published: (2026)

Long-time contractivity estimates for kinetic Kolmogorov-Fokker-Planck equations
by: Forcillo, Nicolò, et al.
Published: (2025)

Optimal regularity for kinetic Fokker-Planck equations in domains
by: Ros-Oton, Xavier, et al.
Published: (2025)

An interacting particle consensus method for constrained global optimization
by: Carrillo, José A., et al.
Published: (2024)

A Neural Score-Based Particle Method for the Vlasov-Maxwell-Landau System
by: Ilin, Vasily, et al.
Published: (2026)

Nonlinear Vlasov-Fokker-Planck equations: From generalized Wasserstein gradient flow to GENERIC structure
by: Liu, Zhenxin, et al.
Published: (2026)

Velocity averaging and Hölder regularity for kinetic Fokker-Planck equations with general transport operators and rough coefficients
by: Zhu, Yuzhe
Published: (2020)

A preconditioned boundary value method for advection-diffusion equations with half Laplacian via spectrum doubling
by: Yuan, Pu, et al.
Published: (2025)

Quantitative Convergence of Wasserstein Gradient Flows of Kernel Mean Discrepancies
by: Chizat, Lénaïc, et al.
Published: (2026)

Convergence of drift-diffusion PDEs arising as Wasserstein gradient flows of convex functions
by: Chizat, Lénaïc, et al.
Published: (2025)

Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce data
by: Gu, Hyemin, et al.
Published: (2022)

Enhancing Future Prediction of Linear and Nonlinear Reduced-Order Models for Transport-Dominated Problems Using Lagrangian Data
by: Li, Meng, et al.
Published: (2026)

Solving nonconvex Hamilton--Jacobi--Isaacs equations with PINN-based policy iteration
by: Yang, Hee Jun, et al.
Published: (2025)

Well-posedness and long-time behavior for self-consistent Vlasov-Fokker-Planck equations with general potentials
by: Gervais, Pierre, et al.
Published: (2024)

Wasserstein-Łojasiewicz inequalities and asymptotics of McKean-Vlasov equation
by: Choi, Beomjun, et al.
Published: (2025)

Optimal-Transport Stability of Inverse Point-Source Problems for Elliptic and Parabolic Equations
by: Qiu, Lingyun, et al.
Published: (2025)

Guaranteeing Higher Order Convergence Rates for Accelerated Wasserstein Gradient Flow Schemes
by: Chu, Raymond, et al.
Published: (2025)

Weak Adversarial Neural Pushforward Method for Fractional Fokker-Planck Equations
by: He, Andrew Qing, et al.
Published: (2026)

Solving the BGK Model and Boltzmann equation by Fourier Neural Operator with conservative constraints
by: Hu, Boyun, et al.
Published: (2025)

Machine Learning-based quadratic closures for non-intrusive Reduced Order Models
by: Codega, Gabriele, et al.
Published: (2025)

A kinetic Nash inequality and precise boundary behavior of the kinetic Fokker-Planck equation
by: Henderson, Christopher, et al.
Published: (2024)

Neural Discovery of Strichartz Extremizers
by: Valenzuela, Nicolás, et al.
Published: (2026)

Trend to equilibrium and hypoelliptic regularity for the relativistic Fokker-Planck equation
by: Arnold, Anton, et al.
Published: (2024)