Common wisdom has it that small distinctions in the probabilities quantifying a belief network do not matter much for the results of probabilistic queries. Yet, one can develop re...
We present a framework for the automatic recognition of complex multi-agent events in settings where structure is imposed by rules that agents must follow while performing activit...
Abstract—A probabilistic kernel approach to pairwise preference learning based on Gaussian processes is applied to predict preference judgments for sound quality degradation mech...
Perry Groot, Tom Heskes, Tjeerd Dijkstra, James M....
We propose a generative model that codes the geometry and appearance of generic visual object categories as a loose hierarchy of parts, with probabilistic spatial relations linkin...
: This paper describes a new approach for the creation of an adaptive system able to selectively combine dynamic multidimensional information sources to perform state estimation. T...