2 papers
math.NA2026
When Rough Data Helps: A Phase Transition in Convergence Rates for Kernel Recovery in Integral Operators
Jihong Wang, Fei Lu, Yue Yu
Learning kernels in operators from data is a fundamental task that arises in nonlocal continuum mechanics, operator learning, and interacting particle systems. A central question i…
cs.LG2024
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators
Yiming Fan, Habib Najm, Yue Yu +2
Nonlocal, integral operators have become an efficient surrogate for bottom-up homogenization, due to their ability to represent long-range dependence and multiscale effects. Howeve…