In this paper, we propose novel algorithms for total variation (TV) based image restoration and parameter estimation utilizing variational distribution approximations. Within the h...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
We propose total subset variation (TSV), a convexity preserving generalization of the total variation (TV) prior, for higher order clique MRF. A proposed differentiable approximat...
One of the key factors for the success of recent energy
minimization methods is that they seek to compute global
solutions. Even for non-convex energy functionals, optimization
...
Petter Strandmark, Fredrik Kahl, Niels Chr. Overga...
Abstract— Design variability due to within-die and die-todie process variations has the potential to significantly reduce the maximum operating frequency and the effective yield...
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...