Sampling-Free Variational Inference for Neural Networks with Multiplicative Activation Noise.
Jannik SchmittStefan RothPublished in: GCPR (2021)
Keyphrases
- variational inference
- neural network
- bayesian inference
- topic models
- probabilistic model
- posterior distribution
- probabilistic graphical models
- gaussian process
- variational methods
- latent dirichlet allocation
- mixture model
- missing data
- closed form
- random sampling
- markov chain monte carlo
- graphical models
- sample size
- noise level
- exponential family
- approximate inference
- factor graphs
- median filter
- multiscale
- pairwise
- optical flow
- markov networks
- probability distribution
- text mining
- markov random field