13 citations · 18 across the 9 of their papers we have counts for
9 papers
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 robust, scalable K-statistic for quantifying immune cell clustering in spatial proteomics data
Julia Wrobel, Hoseung Song
Spatial summary statistics based on point process theory are widely used to quantify the spatial organization of cell populations in single-cell spatial proteomics data. Among thes…
Multivariate Differential Association Analysis
Hoseung Song, Michael C. Wu
Identifying how dependence relationships vary across different conditions plays a significant role in many scientific investigations. For example, it is important for the compariso…
Practical and powerful kernel-based change-point detection
Hoseung Song, Hao Chen
Change-point analysis plays a significant role in various fields to reveal discrepancies in distribution in a sequence of observations. While a number of algorithms have been propo…
New graph-based multi-sample tests for high-dimensional and non-Euclidean data
Hoseung Song, Hao Chen
Testing the equality in distributions of multiple samples is a common task in many fields. However, this problem for high-dimensional or non-Euclidean data has not been well explor…
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…
Generalized Kernel Two-Sample Tests
Hoseung Song, Hao Chen
Kernel two-sample tests have been widely used for multivariate data to test equality of distributions. However, existing tests based on mapping distributions into a reproducing ker…
Asymptotic distribution-free change-point detection for data with repeated observations
Hoseung Song, Hao Chen
In the regime of change-point detection, a nonparametric framework based on scan statistics utilizing graphs representing similarities among observations is gaining attention due t…