End-to-End Trained Energy-Based Model for Image Recovery
This paper presents a novel end-to-end (E2E) empirical Bayes framework for learning the posterior distribution in linear inverse problems. The proposed framework models the log-posterior as the sum of a log-likelihood derived from the known forward model and a neural network-parameterized log-prior learned from trainin...
Jyothi Rikhab Chand, Mathews Jacob
· Journal of Imaging · 0 citations