Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are

Bridging the gap between research and application, Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference provides a concise, and integrated acc

During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the developm

Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard

Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and inf