How Good is the Bayes Posterior in Deep Neural Networks Really?
Florian WenzelKevin RothBastiaan S. VeelingJakub SwiatkowskiLinh TranStephan MandtJasper SnoekTim SalimansRodolphe JenattonSebastian NowozinPublished in: CoRR (2020)
Keyphrases
- reinforcement learning
- neural network
- neural nets
- back propagation
- genetic algorithm
- posterior probability
- support vector
- machine learning
- posterior distribution
- artificial intelligence
- probability distribution
- model averaging
- artificial neural networks
- decision trees
- learning algorithm
- conditionally independent
- feedforward neural networks
- multi layer perceptron
- network architecture
- gaussian process
- training process
- feed forward
- multi layer
- fuzzy logic
- support vector machine
- fuzzy systems
- bayesian framework
- neural network model
- radial basis function
- rule extraction
- unsupervised learning
- cellular neural networks
- information criterion
- bayes optimal
- neural network is trained