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against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
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their added value against simpler machine-learning baselines; train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies
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data. It brings together AI researchers and Digital Humanities scholars to seek solutions to the problem of inadequate data-mining tools we have, aiming to derive information from the continuous stream
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