27 citations · 56 across the 14 of their papers we have counts for
15 papers
Convex geometry of diffusion laws and gradient flows for stochastic control
Yupeng Bai, Louis-Pierre Chaintron, Zhenjie Ren +1
We study gradient-type dynamics for weak stochastic control through the laws of controlled diffusions on path space. Although the objective is generally nonconvex in the drift, a u…
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…
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…
Time-uniform log-Sobolev inequalities and applications to propagation of chaos
Pierre Monmarché, Zhenjie Ren, Songbo Wang
Time-uniform log-Sobolev inequalities (LSI) satisfied by solutions of semi-linear mean-field equations have recently appeared to be a key tool to obtain time-uniform propagation of…
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…
Logarithmic Sobolev inequalities for non-equilibrium steady states
Pierre Monmarché, Songbo Wang
We consider two methods to establish log-Sobolev inequalities for the invariant measure of a diffusion process when its density is not explicit and the curvature is not positive ev…
Uniform-in-time propagation of chaos for kinetic mean field Langevin dynamics
Fan Chen, Yiqing Lin, Zhenjie Ren +1
We study the kinetic mean field Langevin dynamics under the functional convexity assumption of the mean field energy functional. Using hypocoercivity, we first establish the expone…
Mean Field Optimization Problem Regularized by Fisher Information
Julien Claisse, Giovanni Conforti, Zhenjie Ren +1
Recently there is a rising interest in the research of mean field optimization, in particular because of its role in analyzing the training of neural networks. In this paper by add…
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…
Entropic Fictitious Play for Mean Field Optimization Problem
Fan Chen, Zhenjie Ren, Songbo Wang
We study two-layer neural networks in the mean field limit, where the number of neurons tends to infinity. In this regime, the optimization over the neuron parameters becomes the o…
Scalable Quantum Tomography with Fidelity Estimation
Jun Wang, Zhao-Yu Han, Song-Bo Wang +4
We propose a quantum tomography scheme for pure qudit systems which adopts random base measurements and generative learning methods, along with a built-in fidelity estimation appro…