Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings.
John MitrosArjun PakrashiBrian Mac NameePublished in: CoRR (2020)
Keyphrases
- deep learning
- posterior distribution
- probability distribution
- markov chain monte carlo
- posterior probability
- bayesian networks
- machine learning
- unsupervised learning
- bayesian inference
- unsupervised feature learning
- probabilistic model
- mental models
- weakly supervised
- bayesian framework
- parameter estimation
- multi class
- maximum a posteriori