Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting.
Adam D. CobbBrian JalaianPublished in: CoRR (2020)
Keyphrases
- monte carlo
- neural network
- markov chain monte carlo
- monte carlo methods
- bayesian inference
- bayesian networks
- monte carlo simulation
- markov chain
- importance sampling
- particle filter
- markovian decision
- probabilistic inference
- monte carlo tree search
- probabilistic model
- variance reduction
- statistical inference
- adaptive sampling
- matrix inversion
- stochastic approximation
- monte carlo method
- posterior probability
- temporal difference
- maximum likelihood
- game tree
- dynamic programming
- posterior distribution
- hyperparameters
- global illumination
- reinforcement learning
- kalman filter
- point processes
- parameter estimation