Bayesian Inference with Latent Hamiltonian Neural Networks.

Somayajulu L. N. Dhulipala Yifeng Che Michael D. Shields

Published in: CoRR (2022)

Keyphrases

bayesian inference
neural network
probabilistic model
prior information
latent variables
variational inference
bayesian model

hyperparameters
hidden variables
hierarchical bayesian
statistical inference
artificial neural networks
variational bayes
back propagation

markov chain monte carlo
particle filter
gibbs sampler
probabilistic modeling
variational approximation
weighted model counting
bayesian models

prior distribution
markov networks
random variables
maximum likelihood
graphical models
co occurrence
reinforcement learning