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cs.LG2025
Post-Training Augmentation Invariance
Keenan Eikenberry, Lizuo Liu, Yoonsang Lee
This work develops a framework for post-training augmentation invariance, in which our goal is to add invariance properties to a pretrained network without altering its behavior on…
cs.LG2023
Learning In-between Imagery Dynamics via Physical Latent Spaces
Jihun Han, Yoonsang Lee, Anne Gelb
We present a framework designed to learn the underlying dynamics between two images observed at consecutive time steps. The complex nature of image data and the lack of temporal in…