We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
— There are several types of processes which can be modeled explicitly by recording the interactions between a set of actors over time. In such applications, a common objective i...
Abstract— Fast radio wave propagation prediction is of tremendous interest for planning and optimization of cellular radio networks. We propose a cube oriented 3D ray launching a...
—Knowing the dependencies among computing assets and services provides insights into the computing and business landscape, therefore, facilitating low-risk timely changes in supp...
Alexandru Caracas, Andreas Kind, Dieter Gantenbein...
Robustness to illumination variations is a key requirement for the problem of change detection which in turn is a fundamental building block for many visual surveillance applicati...