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arXiv cs.LG
arXiv cs.LG
6/30/2026
scKDGM: KAN-guided Dynamic Graph Masked Learning for Single-Cell RNA-seq Clustering

scKDGM: KAN-guided Dynamic Graph Masked Learning for Single-Cell RNA-seq Clustering

Short summary

scKDGM is a machine learning framework for clustering single-cell RNA-seq data using graph-aware gene masking and KAN-based encoding to handle high-dimensional, sparse data with technical noise. The method outperforms 10 baseline approaches on 12 real datasets, improving NMI and ARI metrics.

  • •Combines masked autoencoders with dynamic graph construction for improved scRNA-seq clustering
  • •Addresses technical challenges: high dimensionality, sparsity, dropout, and measurement noise
  • •Benchmarks demonstrate superior performance over existing methods on multiple genomic datasets

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The original title is about deep learning for scRNA-seq analysis. Let me rewrite it to be punchy and specific while preserving key facts.
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