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Soft Contrastive Learning for Unsupervised Discovery of Phases of Matter
A machine learning (ML) framework for phase-diagram construction in condensed matter systems with unknown phase structure is presented. The method combines physically motivated descriptors with contrastive representation learning and a two-stage data-generation workflow. First, a sparse set of confi
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