This paper investigates the use of the Bayesian inference for devising an unsupervised sketch rendering procedure. As likelihood model of this inference, we exploit the recent sta...
Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...
The paper presents how the Random PROLOG Processor (RPP), a bio-inspired model of computations, can be used for formalization and analysis of a phenomenon - the Collective Intelli...
The impact of process variation in state of the art technology makes traditional (worst case) designs unnecessarily pessimistic, which translates to suboptimal designs in terms of...
Abstract. The (Extended) Kalman filter has been established as a standard method for object tracking. While a constraining motion model stabilizes the tracking results given noisy...
Alexander Barth, Jan Siegemund, Uwe Franke, Wolfga...