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Jaehoon Cha

2 accepted papers

2025

Enhancing Imaging Generation through Implicit Neural Representations and HyperNetwork for Spatial Variability

ICASSP 2025accepted

Collecting data from diverse perspectives is essential across many fields to achieve high-resolution imaging, from Synthetic Aperture Imaging (SAI) to advanced microscopy techniques. However, due to persistent challenges, fully capturing variability in position, angle, and scale remains difficult, d…

Cited by 1SourceScholar
2023

Orthogonality-Enforced Latent Space in Autoencoders: An Approach to Learning Disentangled Representations

ICML 2023poster

Noting the importance of factorizing (or disentangling) the latent space, we propose a novel, non-probabilistic disentangling framework for autoencoders, based on the principles of symmetry transformations that are independent of one another. To the best of our knowledge, this is the first determini…

Cited by 16SourcePDFScholar