Computational and data-driven design of quantum and energy materials - Qimin Yan's Group at Northeastern
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Bandformer
Bandformer PublicImplementation of Graph Transformer Networks for Accurate Band Structure Prediction: An End-to-End Approach
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Configurational-Disorder
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DFCL
DFCL PublicIncorporation of density scaling constraint in density functional design via contrastive representation learning implemented in PyTorch.
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- TSENN Public
Implementation of Accurate Prediction of Tensorial Properties via an Equivariant Neural Network (TSENN)
qmatyanlab/TSENN’s past year of commit activity - CHGCNN Public
qmatyanlab/CHGCNN’s past year of commit activity - Bandformer Public
Implementation of Graph Transformer Networks for Accurate Band Structure Prediction: An End-to-End Approach
qmatyanlab/Bandformer’s past year of commit activity - DisorderGNN Public
qmatyanlab/DisorderGNN’s past year of commit activity - Defect_GNN Public
leveraging persistent homology features to predict defect properties through graph neural networks
qmatyanlab/Defect_GNN’s past year of commit activity - Configurational-Disorder Public
Studying configurational disordering properties through graph neural networks
qmatyanlab/Configurational-Disorder’s past year of commit activity - DFCL Public
Incorporation of density scaling constraint in density functional design via contrastive representation learning implemented in PyTorch.
qmatyanlab/DFCL’s past year of commit activity
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