Maximum Mean Discrepancy (MMD) for Domain Adaptation

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Using the Maximum Mean Discrepancy metric to minimize the distribution shift between feature representations of source and target domains in transfer learning.

Why It Matters

MMD is explicitly used as the mechanism to align feature distributions between the source (simulated) and target (new cells) domains, mitigating the primary challenge of generalization.

Evidence

MMD aligns latent feature distributions between simulated and target domains to mitigate domain shift

Related Papers

• openalex-2603.24475-conformalized-transfer-learning-for-li-ion-battery-state-of