We present a principled Bayesian framework for modeling partial memberships of data points to clusters. Unlike a standard mixture model which assumes that each data point belongs ...
Katherine A. Heller, Sinead Williamson, Zoubin Gha...
We introduce an approach to visualize stationary 2D vector fields with global uncertainty obtained by considering the transport of local uncertainty in the flow. For this, we ex...
We present a novel technique for image inpainting, the problem of filling-in missing image parts. Image inpainting is ill-posed and we adopt a probabilistic model-based approach ...
— We present a robot localization system using biologically-inspired vision. Our system models two extensively studied human visual capabilities: (1) extracting the “gist” of...
Process variations have become a critical issue in performance verification of high-performance designs. We present a new, statistical timing analysis method that accounts for int...