Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications.
Nikolaj Takata MückeBenjamin SanderseSander M. BohtéCornelis W. OosterleePublished in: CoRR (2021)
Keyphrases
- markov chain
- inverse problems
- neural network
- image reconstruction
- steady state
- global optimization
- markov chain monte carlo
- monte carlo method
- monte carlo simulation
- transition probabilities
- convex optimization
- monte carlo
- state space
- stationary distribution
- random walk
- optimization methods
- pattern recognition
- transition matrix
- optimization problems
- generative model
- maximum likelihood
- partial differential equations
- bayesian networks
- early vision
- computer vision
- genetic algorithm
- machine learning
- graphical models
- posterior distribution
- probabilistic model
- high quality
- bayesian learning
- image processing