Model transformations provide a powerful capability to automate model refinements. However, the use of model transformation languages may present challenges to those who are unfami...
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
The Symbolic Probabilistic Inference (SPI) Algorithm [D'Ambrosio, 19891 provides an efficient framework for resolving general queries on a belief network. It applies the conc...
Ross D. Shachter, Bruce D'Ambrosio, Brendan Del Fa...
Adaptor grammars extend probabilistic context-free grammars to define prior distributions over trees with "rich get richer" dynamics. Inference for adaptor grammars seek...
Although MATLAB1 has become one of the mainstream languages for the machine learning community, there is still skepticism among the Grammatical Inference (GI) community regarding t...
Hasan Ibne Akram, Colin de la Higuera, Huang Xiao,...