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cs.LG2026
Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization
Simon Zhang, Ryan P. DeMilt, Kun Jin +1
Out-of-distribution (OoD) generalization occurs when representation learning encounters a distribution shift. This occurs frequently in practice when training and testing data come…
cs.LG2020
The Gaussian Transform
Kun Jin, Facundo Mémoli, Zhengchao Wan
We introduce the Gaussian transform (GT), an optimal transport inspired iterative method for denoising and enhancing latent structures in datasets. Under the hood, GT generates a n…