Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks.
Majd Al AawarSrikar MutnuriMansooreh MontazerinAjitesh SrivastavaPublished in: CoRR (2024)
Keyphrases
- neural network
- prediction accuracy
- pattern recognition
- graph theory
- artificial neural networks to predict
- prediction model
- graph representation
- dynamic model
- graph structure
- neural network ensemble
- prediction algorithm
- global consistency
- graph based algorithm
- graph model
- multi layer perceptron
- bipartite graph
- graph matching
- feed forward
- neural network model
- chaotic time series
- nonlinear dynamics
- directed graph
- recurrent networks
- protein function prediction
- short term prediction
- graph partitioning
- random walk
- wheel slip
- artificial neural networks
- small world
- multi layer
- global structure
- radial basis function network
- graph theoretic
- global information
- directed acyclic graph
- fuzzy systems
- recurrent neural networks
- connected components
- dynamical systems
- social network analysis
- fault diagnosis
- structured data
- back propagation
- fuzzy logic
- genetic algorithm