MRM mixes hidden representations of original and DA-augmented proteins and uses a difficulty scheduler on the beta distribution to produce training samples that balance structural fidelity with diversity.
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Enhancing Protein Representation Learning via Manifold Restore Mixing
MRM mixes hidden representations of original and DA-augmented proteins and uses a difficulty scheduler on the beta distribution to produce training samples that balance structural fidelity with diversity.