In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Symbolic AI systems typically have difficulty reasoning about motion in continuous environments, such as determining whether a cornering car will clear a close obstacle. Bimodal s...
In this paper we combine an integer programming approach and a computer simulation tool to successfully develop and verify an improved classification schedule for a real-world trai...
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
This article presents a new method for non-rigid surface registration between a surface model and a surface of an internal organ in a given 3D medical image. The surface is repres...