Abstract. Over the last decade, first-order constraints have been efficiently used in the artificial intelligence world to model many kinds of complex problems such as: scheduling,...
Abstract. The stochastic satisfiability modulo theories (SSMT) problem is a generalization of the SMT problem on existential and randomized (aka. stochastic) quantification over di...
Tomographic reconstruction from positron emission tomography (PET) data is an ill-posed problem that requires regularization. An attractive approach is to impose an 1-regularizatio...
J. Verhaeghe, Dimitri Van De Ville, I. Khalidov, Y...
Abstract. We extend the setting of Satisfiability Modulo Theories (SMT) by introducing a theory of costs C, where it is possible to model and reason about resource consumption and ...
Abstract. This work addresses a class of total-variation based multilabeling problems over a spatially continuous image domain, where the data fidelity term can be any bounded fun...