Sampling, variational Bayesian inference, and conditioned stochastic differential equations.
Todd P. ColemanMaxim RaginskyPublished in: CDC (2021)
Keyphrases
- variational bayesian inference
- stochastic differential equations
- latent dirichlet allocation
- brownian motion
- bayesian analysis
- maximum a posteriori estimation
- random sampling
- topic models
- monte carlo
- fractional brownian motion
- sample size
- additive gaussian noise
- graphical models
- gaussian distribution
- stochastic process