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Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles
Computational virtual high-throughput screening (VHTS) with density functional theory (DFT) and machine-learning (ML)-acceleration is essential in rapid materials discovery.
Meta Segmentation Network for Ultra-Resolution Medical Images
MSN can fast generate the weights of fusion layers through a simple meta-learner, requiring only a few training samples and epochs to converge.
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