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arXiv Machine Learning By Yupei Zhang, Hao Chen, Li Pan, Chao Li, Xiaohan Xing

Correlation-Guided Flow Matching with Annealed Masking for Spatial Transcriptomics Generation

Read the original on arXiv Machine Learning →

CorrFlow is a new generative framework for predicting spatial transcriptomics from histology images. It explicitly models gene-gene interactions using an annealed masked flow matching strategy and a gene graph‑regularized optimization that incorporates prior knowledge from STRING and data‑driven co‑expression from WGCNA. Across 12 datasets, CorrFlow outperforms existing methods in average PCC and HPCC, producing more biologically coherent ST predictions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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