CS-ARM-BN uses negative control samples to stabilize Batch Normalization statistics in a meta-learning framework, achieving robust MoA classification on new experimental batches under label shift and small sample sizes.
R., Haque, I., and Earnshaw, B
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Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls
CS-ARM-BN uses negative control samples to stabilize Batch Normalization statistics in a meta-learning framework, achieving robust MoA classification on new experimental batches under label shift and small sample sizes.