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05/18/2023
Small noise analysis for Tikhonov and RKHS regularizations
Regularization plays a pivotal role in ill-posed machine learning and in...
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12/29/2022
A Data-Adaptive Prior for Bayesian Learning of Kernels in Operators
Kernels are efficient in representing nonlocal dependence and they are w...
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03/08/2022
Data adaptive RKHS Tikhonov regularization for learning kernels in operators
We present DARTR: a Data Adaptive RKHS Tikhonov Regularization method fo...
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06/10/2021
Identifiability of interaction kernels in mean-field equations of interacting particles
We study the identifiability of the interaction kernels in mean-field eq...
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10/29/2020
