7 citations · 15 across the 7 of their papers we have counts for
8 papers
Learning Multi-type heterogeneous interacting particle systems
Quanjun Lang, Xiong Wang, Fei Lu +1
We propose a framework for the joint inference of network topology, multi-type interaction kernels, and latent type assignments in heterogeneous interacting particle systems from m…
Self-test loss functions for learning weak-form operators and gradient flows
Yuan Gao, Quanjun Lang, Fei Lu
The construction of loss functions presents a major challenge in data-driven modeling involving weak-form operators in PDEs and gradient flows, particularly due to the need to sele…
Interacting Particle Systems on Networks: joint inference of the network and the interaction kernel
Quanjun Lang, Xiong Wang, Fei Lu +1
Modeling multi-agent systems on networks is a fundamental challenge in a wide variety of disciplines. Given data consisting of multiple trajectories, we jointly infer the (weighted…
Small noise analysis for Tikhonov and RKHS regularizations
Quanjun Lang, Fei Lu
Regularization plays a pivotal role in ill-posed machine learning and inverse problems. However, the fundamental comparative analysis of various regularization norms remains open.…
A Data-Adaptive Prior for Bayesian Learning of Kernels in Operators
Neil K. Chada, Quanjun Lang, Fei Lu +1
Kernels are efficient in representing nonlocal dependence and they are widely used to design operators between function spaces. Thus, learning kernels in operators from data is an…
Data adaptive RKHS Tikhonov regularization for learning kernels in operators
Fei Lu, Quanjun Lang, Qingci An
We present DARTR: a Data Adaptive RKHS Tikhonov Regularization method for the linear inverse problem of nonparametric learning of function parameters in operators. A key ingredient…
Identifiability of interaction kernels in mean-field equations of interacting particles
Quanjun Lang, Fei Lu
This study examines the identifiability of interaction kernels in mean-field equations of interacting particles or agents, an area of growing interest across various scientific and…
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…