1 citations · 1 across the 7 of their papers we have counts for
4 papers · 1 filter
Wasserstein Bounds for Ambient and Latent Smoothing on Data Manifolds
Wonjun Lee, Wenyan Luo
Smoothing empirical data can fill gaps between observations, while noise in the surrounding space can move mass away from the manifold supporting the data. We derive Wasserstein er…
Dynamics Over Landscape: The Emergence of Linear Separability via Spectral Alignment in Contrastive Learning
Jeff Calder, Wonjun Lee
Contrastive learning effectively clusters data despite a loss landscape filled with poor solutions, a success that is heavily dependent on the choice of data augmentations. How opt…
Geometry-Preserving Encoder/Decoder in Latent Generative Models
Wonjun Lee, Riley C. W. O'Neill, Dongmian Zou +2
Generative modeling aims to generate new data samples that resemble a given dataset. When using diffusion models for this task, one of the main challenges is solving the problem in…
Monotone discretizations of levelset convex geometric PDEs
Jeff Calder, Wonjun Lee
We introduce a novel algorithm that converges to level-set convex viscosity solutions of high-dimensional Hamilton-Jacobi equations. The algorithm is applicable to a broad class of…