Co-occurring keywords · papers mentioning both
mean-field langevin dynamics
(4)
wasserstein distance
(3)
neural network
(2)
particle approximation
(2)
two-layer neural network
(2)
stein variational gradient descent
(2)
stochastic differential equation
(2)
mean field theory
(2)
stochastic gradient descent
(2)
mean-field stochastic differential equation
(1)
Papers
Beyond propagation of chaos: A stochastic algorithm for mean field optimization
COLT 2025
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
ICLR 2025
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
ICML 2025
Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD
ICML 2024
Improved Particle Approximation Error for Mean Field Neural Networks
NeurIPS 2024
Mean-field Chaos Diffusion Models
ICML 2024
Sampling from the Mean-Field Stationary Distribution
COLT 2024
Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems
ICLR 2024
Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
NeurIPS 2023
Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics
ICLR 2023
Quantitative Propagation of Chaos for SGD in Wide Neural Networks
NeurIPS 2020