Papers/2609.16207
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Hyperbolic Contrastive Learning with Entailment for Spatial Transcriptomics

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contrastive learningspatial transcriptomicsgene expressionhyperbolic geometry
2609.16207
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Abstract

The paper presents a novel hyperbolic contrastive learning model that enhances gene expression prediction in Spatial Transcriptomics by addressing issues of over-smoothing and uniformity in predictions.

Reality Card

Core Claim

HyCLoST achieves a 6% reduction in MSE and an 8% increase in PCC across 26 ST datasets compared to previous methods.

Method / Result

6% reduction in MSE and 8% increase in PCC

Limitations

High operational costs and specialized equipment requirements limit accessibility and scalability of Spatial Transcriptomics.

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