Recent advances in computer graphics have produced images approaching the elusive goal of photorealism. Since many natural objects are so complex and detailed, they are often not ...
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
We investigate the task of compressing an image by using different probability models for compressing different regions of the image. In an earlier paper, we introduced a class of...
We consider the estimation problem in Gaussian graphical models with arbitrary structure. We analyze the Embedded Trees algorithm, which solves a sequence of problems on tractable...
Venkat Chandrasekaran, Jason K. Johnson, Alan S. W...