7 citations · 15 across the 7 of their papers we have counts for
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stat.ML2022★ 1 cited
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…
stat.ML2022★ 2 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…