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Youngmi Heo
연세대학교 수학과
Applied and Computational Harmonic Analysis
yhur@yonsei.ac.kr
Constructing multi-dimensional wavelets and their extensions and variants, with focus on solving problems beyond tensor product methods using tools from Algebra and Algebraic Geometry.
Developing wavelet-based signal processing methods for biological and manufacturing data, and exploring integration of wavelets with Deep Learning for data-driven wavelet filter construction.
Describing quantum field theory using wavelets, particularly for quark and gluon fields confined in hadrons, leveraging wavelets' localization properties over Fourier expansion.
Provable wavelet-based neural approximation
Design of wavelet filter banks for any dilation using extended Laplacian pyramid matrices
Detail loss in super-resolution models based on the Laplacian pyramid
Wavelet series expansion in Hardy spaces with approximate duals
Simplifying formal proof-generating models with ChatGPT and basic searching techniques
Laplacian pyramid-like autoencoder
Spectral bias reduction using wavelet bases with rigorous analysis
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