ParamRepulsor
Parametric embeddings with stronger preservation of local structure.
ParamRepulsor addresses the loss of local detail in parametric dimensionality reduction. It combines hard negative mining with a strongly repulsive loss to improve local structure while retaining global relationships and the ability to embed unseen data.
This work, with Yingfan Wang and Cynthia Rudin, appeared at NeurIPS 2024.