We explore the possibility of using Stochastic Bracketing Linear Inversion Transduction Grammars for a full-scale German–English translation task, both on their own and in conjunction with alignments induced with GIZA++. The rationale for transduction grammars, the details of the system and some results are presented.

Stochastic Inversion Transduction Grammars constitute a powerful formalism in Machine Translation for which an efficient Dynamic Programming parsing algorithm exists. In this work, we review this parsing algorithm and propose important modifications that enlarge the search space. These modifications allow the parsing algorithm to search for more and better solutions.

The ensemble Kalman inversion (EKI) method is a for the estimation of unknown parameters in context (Bayesian) inverse problems. approximates underlying measure by an particles and iteratively applies update to evolve (the approximation the) prior into posterior measure. For convergence analysis EKI it common practice derive continuous version, replacing iteration with stochastic differential e...

An important problem that is related to phrase-based statistical translation models is the obtaining of word phrases from an aligned bilingual training corpus. In this work, we propose obtaining word phrases by means of a Stochastic Inversion Translation Grammar. Experiments on the shared task proposed in this workshop with the Europarl corpus have been carried out and good results have been ob...

We introduce an approach for the stochastic characterization of geometric and hydraulic parameters a three-dimensional (3D) discrete fracture network (DFN) estimating their uncertainty based on data from tomography experiments. The inversion relies Bayesian framework resulting posterior distribution is characterized by generating samples Markov chain Monte Carlo (MCMC) methods. method evaluated...