Graph neural networks for the prediction of molecular structure-property relationships.
Jan G. RittigQinghe GaoManuel DahmenAlexander MitsosArtur M. SchweidtmannPublished in: CoRR (2022)
Keyphrases
- molecular structure
- neural network
- prediction accuracy
- artificial neural networks to predict
- neural network ensemble
- pattern recognition
- graph properties
- graph matching
- directed acyclic graph
- protein function prediction
- structural patterns
- prediction algorithm
- radial basis function network
- causal relationships
- bipartite graph
- prediction model
- neural nets
- artificial neural networks
- back propagation
- directed graph
- prediction error
- graph model
- structured data
- multi layer perceptron
- graph representation
- learning algorithm
- connected components
- global consistency
- neural network model
- graph databases
- radial basis function
- radial basis function neural network
- graph structures
- undirected graph
- feed forward
- graph structure
- chaotic time series
- image segmentation
- neural networks and support vector machines
- graph theory