DISTAL: Distillation and Self-Supervised Pretraining for Structure-Agnostic Materials Property Prediction
DISTAL is a dual-prior framework for structure-agnostic materials property prediction that combines self-supervised compositional pretraining with structure-aware knowledge distillation and achieves the strongest overall performance among all evaluated feature combinations.
Wei-Ran Wang, Xin-Tong Huo, Yue-Ying Wang et al.
· 0 citations