9 papers
Large-scale concentration and relaxation for mean-field Langevin particle systems
Songbo Wang
We study the Langevin dynamics of diffusive particles with regular pairwise interactions under mean-field scaling. By approximating empirical distributions with conditional distrib…
Rethinking Semi-Supervised Node Classification with Self-Supervised Graph Clustering
Songbo Wang, Renchi Yang, Yurui Lai +2
The emergence of graph neural networks (GNNs) has offered a powerful tool for semi-supervised node classification tasks. Subsequent studies have achieved further improvements throu…
Uniform-in-time propagation of chaos for mean field Langevin dynamics
Fan Chen, Zhenjie Ren, Songbo Wang
We study the mean field Langevin dynamics and the associated particle system. By assuming the functional convexity of the energy, we obtain the -convergence of the marginal di…
Size of chaos for Gibbs measures of mean field interacting diffusions
Zhenjie Ren, Songbo Wang
We investigate Gibbs measures for diffusive particles interacting through a two-body mean field energy. By identifying a gradient structure for the conditional law, we derive sharp…
Sharp local propagation of chaos for mean field particles with kernels
Songbo Wang
We present two methods to obtain local propagation of chaos bounds for diffusive particles in mean field interaction. This extends the recent finding…
Self-interacting approximation to McKean-Vlasov long-time limit: a Markov chain Monte Carlo method
Kai Du, Zhenjie Ren, Florin Suciu +1
For a certain class of McKean-Vlasov processes, we introduce proxy processes that substitute the mean-field interaction with self-interaction, employing a weighted occupation measu…