Sample-efficient active learning for materials informatics using integrated posterior variance

· · 来源:dev资讯

"Or consider pipeTo(). Each chunk passes through a full Promise chain: read, write, check backpressure, repeat. An {value, done} result object is allocated per read. Error propagation creates additional Promise branches.

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A device based on light-confining materials can modify superconductivity using quantum fluctuations, without the need for external illumination.

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