Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library ...
The targeted design of functional materials often requires the concurrent optimization of multiple interdependent properties. For boron-doped graphene (BDG), both the band gap and work function ...
Abstract: In this work, we focus on the task of learning the promising graph for clustering and present a novel Tensorized Graph Learning (TGL) framework, which synergizes the neighbor and ...
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