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

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Available model flags: --110m, --tdt-600m, --rnnt-600m, --sortformer. All Google Benchmark flags (--benchmark_filter, --benchmark_format=json, --benchmark_repetitions=N) are passed through.

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