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20112022
most citedLearning interaction kernels in mean-field equations of 1st-order systems of interacting particles

7 citations · 19 across the 8 of their papers we have counts for

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5 papers · 1 filter

stat.ML20223 cited

Nonparametric learning of kernels in nonlocal operators

Fei Lu, Qingci An, Yue Yu

Nonlocal operators with integral kernels have become a popular tool for designing solution maps between function spaces, due to their efficiency in representing long-range dependen…

stat.ML20222 cited

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…

stat.ML2020

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…

stat.ML20207 cited

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…

stat.ML2019

Learning interaction kernels in heterogeneous systems of agents from multiple trajectories

Fei Lu, Mauro Maggioni, Sui Tang

Systems of interacting particles or agents have wide applications in many disciplines such as Physics, Chemistry, Biology and Economics. These systems are governed by interaction l…