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Classroom Contents
MCMC Training of Bayesian Neural Networks
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- 1 Introduction
- 2 Background
- 3 Outline
- 4 Bayesian Neural Networks
- 5 Nonbasing training
- 6 Bayesian approach
- 7 Prior distribution
- 8 Smooth functions
- 9 Symmetric stable distributions
- 10 Standard deviation
- 11 Hyperparameters
- 12 Prediction
- 13 Benefits
- 14 Bayesian inference
- 15 Markov chain Monte Carlo
- 16 Hamiltonian Monte Carlo
- 17 Flexible Bayesian Modeling Software
- 18 Virus Bioresponse
- 19 Training Validation Errors
- 20 Predictive Performance
- 21 CFAR 10 Training
- 22 Questions
