AI RESEARCH
A Hierarchical Sheaf Spectral Embedding Framework for Single-Cell RNA-seq Analysis
arXiv CS.LG
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ArXi:2603.26858v1 Announce Type: new Single-cell RNA-seq data analysis typically requires representations that capture heterogeneous local structure across multiple scales while remaining stable and interpretable. In this work, we propose a hierarchical sheaf spectral embedding (HSSE) framework that constructs informative cell-level features based on persistent sheaf Laplacian analysis. Starting from scale-dependent low-dimensional embeddings, we define cell-centered local neighborhoods at multiple resolutions.