Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...