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Describe Molecules by a Heterogeneous Graph Neural Network ..:

Daiguo Deng (10824002) ; Zengrong Lei (9624150) ; Xiaobin Hong (6562769)..
https://figshare.com/articles/journal_contribution/Describe_Molecules_by_a_Heterogeneous_Graph_Neural_Network_with_Transformer-like_Attention_for_Supervised_Property_Predictions/18857980. , 2022

Link: https://doi.org/10.1021/acsomega.1c06389.s001

RT Journal
T1 <Title>Describe Molecules by a Heterogeneous Graph Neural Network with Transformer-like Attention for Supervised Property Predictions</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_18857980&Exemplar=1&LAN=DE
				
A1 Daiguo Deng (10824002)
A1 Zengrong Lei (9624150)
A1 Xiaobin Hong (6562769)
A1 Ruochi Zhang (9189695)
A1 Fengfeng Zhou (9927)
YR 2022
K1 Biotechnology
K1 Space Science
K1 Biological Sciences not elsewhere classified
K1 Mathematical Sciences not elsewhere classified
K1 Chemical Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 test splitting details
K1 natural language processing
K1 https :// github
K1 graph neural network
K1 art prediction performance
K1 principle study demonstrated
K1 molecule graph may
K1 transformer reading function
K1 molecular property predictions
K1 molecular property
K1 molecule using
K1 molecular structure
K1 study represented
K1 source code
K1 rapid development
K1 new level
K1 molhgt )
K1 like attention
K1 hidden states
K1 existing studies
K1 different types
K1 describe molecules
K1 deep learning
K1 better represent
JF https://figshare.com/articles/journal_contribution/Describe_Molecules_by_a_Heterogeneous_Graph_Neural_Network_with_Transformer-like_Attention_for_Supervised_Property_Predictions/18857980
LK http://dx.doi.org/https://doi.org/10.1021/acsomega.1c06389.s001
DO https://doi.org/10.1021/acsomega.1c06389.s001
SF ELIB - SuUB Bremen

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