German has a richer system of inflectional morphology than English, which causes problems for current approaches to statistical word alignment. Using Giza++ as a reference implementation of the IBM Model 1, an HMMbased alignment and IBM Model 4, we measure the impact of normalizing inflectional morphology on German-English statistical word alignment. We demonstrate that normalizing inflectional...

Feynman-Kac models arise in a large variety of scientific disciplines including physics, chemistry and signal processing. Their mean field particle interpretations, termed commonly Sequential Monte Carlo or Particle Filters, have found numerous applications as they allow to sample approximately from sequences of complex probability distributions and estimate their associated normalizing constan...

The isolation of pure samples quark and gluon jets is key interest at hadron colliders. Recent work has employed topic modeling to disentangle the underlying distributions in mixed obtained from experiments. However, current implementations do not scale high-dimensional observables as they rely on binning data. In this we introduce TopicFlow, a method based normalizing flows learn jet datasets....

? Abstract. In previous papers, the authors studied normalization relative to desirable sets S of`partial results', where it is shown that such sets must be stable. For example, the sets of normal forms, head-normal-forms, and weak head-normal-forms in the-calculus, are all stable. They showed that, for any stable S, S-needed reductions are S-normalizing. This paper continues the investigation ...

This paper deals with a computational aspect of the Bayesian analysis of statistical models with intractable normalizing constants. In the presence of intractable normalizing constants in the likelihood function, traditional MCMC methods cannot be applied. We propose here a general approach to sample from such posterior distributions that bypasses the computation of the normalizing constant. Ou...