2025/02/22 by Tamal K. Dey, Dey, Tamal K., Shreyas N. Samaga +1 · 1 citation
Computer Science · #Algebraic Topology (math.AT) #FOS: Computer and information sciences #FOS: Mathematics #Image Retrieval and Classification Techniques #Machine Learning (cs.LG) #Topological and Geometric Data Analysis
paper · pdf · doi:10.48550/arxiv.2502.16049
openalex publication_date 2025/02/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we propose Quasi Zigzag Persistent Homology (QZPH) as a framework for analyzing time-varying data by integrating multiparameter persistence and zigzag persistence. To this end, we introduce a stable topological invariant that captures both static and dynamic features at different scales. We present an algorithm to compute this invariant efficiently. We show that it enhances the machine learning models when applied to tasks such as sleep-stage detection, demonstrating its effectiveness in capturing the evolving patterns in time-varying datasets.