Do Bayesian Neural Networks Need To Be Fully Stochastic?
Mrinank SharmaSebastian FarquharEric NalisnickTom RainforthPublished in: CoRR (2022)
Keyphrases
- neural network
- monte carlo sampling
- hopfield neural network
- pattern recognition
- maximum likelihood
- artificial neural networks
- back propagation
- bayesian decision
- stochastic nature
- stochastic optimization
- learning automata
- genetic algorithm
- data sets
- feed forward
- associative memory
- bayesian networks
- bayesian analysis
- fuzzy logic
- stochastic model
- monte carlo
- data driven
- feedforward neural networks
- computational intelligence
- bayesian estimation
- stochastic processes
- gaussian processes
- network architecture
- bayesian inference
- neural nets
- neural network model
- radial basis function