1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2024
TUNE: Algorithm-Agnostic Inference after Changepoint Detection
Yinxu Jia, Jixuan Liu, Guanghui Wang +2
In multiple changepoint analysis, assessing the uncertainty of detected changepoints is crucial for enhancing detection reliability -- a topic that has garnered significant attenti…
stat.ME2023
Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation
Hui Chen, Yinxu Jia, Guanghui Wang +1
Accurately detecting multiple change-points is critical for various applications, but determining the optimal number of change-points remains a challenge. Existing approaches based…
stat.ME2023★ 1 cited
Zipper: Addressing degeneracy in algorithm-agnostic inference
Geng Chen, Yinxu Jia, Guanghui Wang +1
The widespread use of black box prediction methods has sparked an increasing interest in algorithm/model-agnostic approaches for quantifying goodness-of-fit, with direct ties to sp…