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Finally, a meta-learning approach that uses readily available negative control samples can close the persistent domain gap in biomedical imaging, making deep learning models practically usable across different experimental batches.
Achieve up to 7% performance gains in out-of-distribution simulation tasks by adapting high-dimensional surrogates at test time using D-optimal statistics.
