There is a growing use of neural network classifiers as unbinned, high-dimensional (and variable-dimensional) reweighting functions. To date, the focus has been on marginal reweighting, where subset features are used for while all other integrated over. some situations, though, it preferable to condition auxiliary instead marginalizing over them. In this paper, we introduce conditional which ex...

Beginning from massive binaries in the Galaxy we evolve black–hole, neutron–star binaries and binary neutron stars, such as the Hulse–Taylor system PSR 1913+16. The new point in our evolution is a quantitative calculation of the accretion of matter by a neutron star in common envelope evolution which sends it into a black hole. We calculate the mass of the latter to be ∼ 2.4 M⊙. The black hole ...

We discuss an interpretation of the Mixture Transition Distribution (MTD) for discretevalued time series which is based on a sequence of independent latent variables which are occasion-specific. We show that, by assuming that this latent process follows a first order Markov Chain, MTD can be generalized in a sensible way. A class of models results which also includes the Hidden Markov Model (HM...

This paper provides new algorithms for computing consistent and partially consistent extensions of information systems. A maximal consistent extension of a given information system includes only objects corresponding to known attribute values which are consistent with all rules extracted from the original information system. A partially consistent extension of a given information system include...