5 papers
Self-fictitious-play for Potential Monotone Ergodic Mean-field Games
Yupeng Bai, Mathieu Laurière, Zhenjie Ren +1
We investigate long-time learning in ergodic, potential, monotone mean-field games (MFGs) via a self-fictitious-play (SFP) dynamics coupling an optimally controlled diffusion with…
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…
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…
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…
Uniform log-Sobolev inequalities for mean field particles with flat-convex energy
Songbo Wang
The purpose of this short note is to demonstrate uniform logarithmic Sobolev inequalities for the mean field gradient particle systems associated to an energy functional that is co…