Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
John P. Cunningham, Krishna V. Shenoy, Maneesh Sah...
We propose to enhance the capabilities of the human visual system by performing optical image processing directly on an observed scene. Unlike previous work which additively super...
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
"A random or stochastic process is a mathematical model for a phenomenon
that evolves in time in an unpredictable manner from the viewpoint of the
observer. The phenomenon m...
Semantic preorders between processes are usually applied in practice to model approximation or implementation relationships. For interactive models these preorders depend crucially...