Recently, constraint-programming techniques have been used to generate test data and to verify the conformity of a program with its specification. Constraint generated for these ta...
We present a general framework to incorporate prior knowledge such as heuristics or linguistic features in statistical generative word alignment models. Prior knowledge plays a ro...
Traditional scenario of probabilistic modelling is directed at generating samples having a given probability distribution. We argue that this scenario is impracticable for image m...
A directed generative model for binary data using a small number of hidden continuous units is investigated. A clipping nonlinearity distinguishes the model from conventional prin...
In this paper, we present a rewriting framework for modeling molecular complexes, biochemical reaction rules, and generation of biochemical networks based on the representation of...