scSiameseClu Sets New SOTA on Unsupervised Single‑Cell Clustering Across 7 Datasets
The paper introduces scSiameseClu, a Siamese clustering framework that combines dual augmentation, siamese fusion, and optimal‑transport clustering to overcome representation collapse in scRNA‑seq data, and demonstrates state‑of‑the‑art performance on seven diverse single‑cell datasets and downstream annotation tasks.
