Moore-Sloan Seed Grant: “Development of a Sample-based Modulated Wasserstein Distance for Heterogeneous Datasets of Unknown Distributions for Small Feature Change Detection”

Prof. Debra Laefer and Prof. Esteban Tabak from NYU’s Courant Institute were awarded seed funding from the Moore-Sloan Foundation to pursue “Development of a Sample-based Modulated Wasserstein Distance for Heterogeneous Datasets of Unknown Distributions for Small Feature Change Detection”. The grant supports a graduate student to work with the two professors on the development of this research project. To learn more about this work, please see the project page here.