Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference techniques. We introduce Church, a universal langu...
Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy,...
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
In many applications of natural language processing (NLP) grammatically tagged corpora are needed. Thus Part of Speech (POS) Tagging is of high importance in the domain of NLP. Ma...
One of the major problems in question answering (QA) is that the queries are either too brief or often do not contain most relevant terms in the target corpus. In order to overcom...
Abstract. The paper proposes a simulation-based method for validating analog and mixed-signal circuits, using the hybrid systems methodology. This method builds upon RRT (Rapidly-e...