From the 1 of 4 linked papers with an AI index.
2 citations · 2 across the 2 of their papers we have counts for
4 papers
A robust, scalable K-statistic for quantifying immune cell clustering in spatial proteomics data
Julia Wrobel, Hoseung Song
The paper introduces KAMP, a method that adjusts Ripley's K statistic for spatial inhomogeneity in single‑cell proteomics data, providing robust clustering and colocalization measu…
Adaptive spatial blocking for scalable clustering inference with applications to high-throughput spatial proteomics
Mingyu Go, Julia Wrobel, Hoseung Song
Ripley's K-function is a widely used spatial summary statistic for assessing clustering in point patterns. However, existing K-based methods can be computationally prohibitive for…
Change-Point Detection With Multivariate Repeated Measures
Serim Han, Jingru Zhang, Hoseung Song
Graph-based methods have shown particular strengths in change-point detection (CPD) tasks for high-dimensional nonparametric settings. However, existing CPD research has rarely add…
A fast and effective kernel two-sample test for large-scale data
Hoseung Song, Hao Chen
Kernel two-sample tests have been widely used, and the development of efficient methods for high-dimensional, large-scale data is receiving increasing attention in the big data era…