Author

Bongseok Kim

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#machine learning Preprint Feb 2025

Active Learning with Bayesian Multi-Fidelity Laplace Neural Operators for Oscillatory Parametric PDEs

Results demonstrate that Bayesian multi-fidelity LNOs, combined with uncertainty-guided active learning, provide a data-efficient framework for operator learning in engineering dynamical systems.

Bongseok Kim, Hao-Yang Zheng, Michael Penwarden et al. · 2 citations

Preprint Aug 2026

FAST-DeepONet: Factor-Augmented Branch Representations for High-Dimensional PDE Inputs in the Small-Sample Regime

FAST-DeepONet, a branch representation combining a fixed spectral path with a regularized projection of the orthogonal residual, in which the directional penalty acts on the effective residual map after each of its rows is normalized, is introduced.

J. Kwon, Bongseok Kim, Guang Lin · 0 citations