Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
Dominik Jain, Bernhard Kirchlechner, Michael Beetz
When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models. One is based on the co...
Interactive image segmentation traditionally involves the
use of algorithms such as Graph Cuts or Random Walker.
Common concerns with using Graph Cuts are metrication
artifacts ...
We present an algorithm for computing the probability density function of the product of two independent random variables, along with an implementation of the algorithm in a compu...
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...