GAN generators can act as priors for Bayesian inference on high-dimensional fields with complex distributions, demonstrated on a heat conduction inverse problem.
Malinverno, Parsimonious Bayesian Markov chain Monte Carlo in- version in a nonlinear geophysical problem, Geophysical Journal Inter- national 151 (2002) 675–688
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Bayesian Inference with Generative Adversarial Network Priors
GAN generators can act as priors for Bayesian inference on high-dimensional fields with complex distributions, demonstrated on a heat conduction inverse problem.