Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
We present a novel approach to image segmentation using iterated Graph Cuts based on multi-scale smoothing. We compute the prior probability obtained by the likelihood from a color...
We motivate and analyse a new Tree Search algorithm, based on recent advances in the use of Gaussian Processes for bandit problems. We assume that the function to maximise on the ...
We consider two stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian Process formulation of regression in which we use the cur...
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
Christian Plagemann, Sebastian Mischke, Sam Prenti...