Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators.
Zongren ZouXuhui MengGeorge Em KarniadakisPublished in: CoRR (2023)
Keyphrases
- neural network
- network architecture
- sensory inputs
- pattern recognition
- neural model
- neural learning
- measurement noise
- connectionist models
- neural network model
- associative memory
- fuzzy logic
- dea models
- noisy environments
- learning rules
- recurrent neural networks
- radial basis function
- back propagation
- artificial neural networks
- genetic algorithm
- multi layer perceptron
- fuzzy systems
- multi layer
- uncertain data
- multilayer perceptron
- missing data
- bio inspired
- decision theory
- feedforward neural networks
- noise free
- self organizing maps
- noisy data
- training process
- hebbian learning
- neural models
- neural architectures
- recurrent networks
- possibility theory
- feed forward neural networks
- belief functions
- feed forward
- conditional probabilities
- artificial intelligence
- machine learning