Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Probabilistic inference was shown effective in non-deterministic diagnosis of end-to-end service failures. Since exact probabilistic diagnosis is known to be an NP-hard problem, a...
NiMo (Nets in Motion) is a visual environment aimed to support totally graphic programming in Data Flow style, with a strong functional inspiration. Solutions of growing complexit...
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
Penalty approaches can be used to efficiently resolve collisions of dynamically simulated rigid and deformable objects. These methods compute penalty forces based on the penetrati...
Bruno Heidelberger, Matthias Teschner, Richard Kei...