4 citations · 6 across the 3 of their papers we have counts for
4 papers · 1 filter
Data-driven Learning of Interaction Laws in Multispecies Particle Systems with Gaussian Processes: Convergence Theory and Applications
Jinchao Feng, Charles Kulick, Sui Tang
We develop a Gaussian process framework for learning interaction kernels in multi-species interacting particle systems from trajectory data. Such systems provide a canonical settin…
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model
Jinchao Feng, Sui Tang
In this paper, we investigate the data-driven identification of asymmetric interaction kernels in the Motsch-Tadmor model based on observed trajectory data. The model under conside…
Data-Driven Model Selections of Second-Order Particle Dynamics via Integrating Gaussian Processes with Low-Dimensional Interacting Structures
Jinchao Feng, Charles Kulick, Sui Tang
In this paper, we focus on the data-driven discovery of a general second-order particle-based model that contains many state-of-the-art models for modeling the aggregation and coll…
Learning particle swarming models from data with Gaussian processes
Jinchao Feng, Charles Kulick, Yunxiang Ren +1
Interacting particle or agent systems that display a rich variety of swarming behaviours are ubiquitous in science and engineering. A fundamental and challenging goal is to underst…