This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
Processor cores embedded in systems-on-a-chip (SoCs) are often deployed in critical computations, and when affected by faults they may produce dramatic effects. When hardware harde...
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
Abstract: The problem of global illumination is virtually synonymouswith solving the rendering equation. Although a great deal of research has been directed toward Monte Carlo and ...