115 citations · 519 across the 28 of their papers we have counts for
4 papers · 1 filter
On the coercivity condition in the learning of interacting particle systems
Zhongyang Li, Fei Lu
In the learning of systems of interacting particles or agents, coercivity condition ensures identifiability of the interaction functions, providing the foundation of learning by no…
Learning interaction kernels in mean-field equations of 1st-order systems of interacting particles
Quanjun Lang, Fei Lu
We introduce a nonparametric algorithm to learn interaction kernels of mean-field equations for 1st-order systems of interacting particles. The data consist of discrete space-time…
Data-driven model reduction for stochastic Burgers equations
Fei Lu
We present a class of efficient parametric closure models for 1D stochastic Burgers equations. Casting it as statistical learning of the flow map, we derive the parametric form by…
Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories
Fei Lu, Mauro Maggioni, Sui Tang
We consider stochastic systems of interacting particles or agents, with dynamics determined by an interaction kernel which only depends on pairwise distances. We study the problem…