Exploring Augmentation-Driven Invariances for Graph Self-supervised Learning in Spatial Omics
Lovro Rabuzin, Michel Tarnow, Valentina Boeva
This study evaluates how different graph augmentations affect embedding quality and downstream performance in spatial omics, showing that well-designed augmentations improve results while poor ones can harm performance.
bioRxiv · Sep 23, 2025 · PreprintBioinformatics