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scTrilemma: Balancing Identity, Invariance, and Fidelity in Single-Cell Representation Learning
Single-cell RNA-seq representation learning is fundamentally label-free: cell identities, states, and contexts are not fixed training targets, so what constitutes signal or nuisance is analysis-dependent. A single representation must therefore preserve biological identity and state, remain robust to
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