DISTAL: Distillation and Self-Supervised Pretraining for Structure-Agnostic Materials Property Prediction
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arXiv:2609.00059v1 Announce Type: new Abstract: Materials property prediction remains difficult in low-data settings, where many target properties are supported by only a limited number of labeled samples. Models with the strongest predictive accuracy often depend on crystal structures, which restr…
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- 2026-09-02 04:00 · arXiv cs.LG
DISTAL: Distillation and Self-Supervised Pretraining for Structure-Agnostic Materials Property Prediction