Most classical scheduling formulations assume a fixed and known duration for each activity. In this paper, we weaken this assumption, requiring instead that each duration can be ...
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Generating vehicle trajectories from video data is an important application of ITS (Intelligent Transportation Systems). We introduce a new tracking approach which uses model-base...
—This paper presents a study of possible extensions of Pathway Logic to represent and reason about semiquantitative and probabilistic aspects of biological processes. The underly...