Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction.
Roy BenjaminUriel SingerKira RadinskyPublished in: CIKM (2022)
Keyphrases
- neural network
- protein function prediction
- prediction accuracy
- artificial neural networks to predict
- prediction model
- neural network ensemble
- graph representation
- graph properties
- prediction algorithm
- pattern recognition
- global consistency
- back propagation
- graph structure
- drug design
- graph model
- fuzzy logic
- artificial neural networks
- graph theory
- prediction error
- neural networks and support vector machines
- connected components
- protein structure prediction
- bipartite graph
- anti monotonic
- self organizing maps
- active learning
- chaotic time series
- interaction networks
- directed acyclic graph
- dna computing
- radial basis function neural network
- graph partitioning
- graph mining
- multi layer
- recurrent neural networks
- neural network model
- directed graph
- three dimensional