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      Bayesian uncertainty quantification and propagation in molecular dynamics simulations 

      Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P. (2012)
      A comprehensive Bayesian probabilistic framework is developed for quantifying and calibrating the uncertainties in the parameters of the models (e.g. force-field potentials) involved in molecular dynamics (MD) simulations ...
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      Hiding sensitive knowledge without side effects 

      Gkoulalas-Divanis, A.; Verykios, V. S. (2009)
      Sensitive knowledge hiding in large transactional databases is one of the major goals of privacy preserving data mining. However, it is only recently that researchers were able to identify exact solutions for the hiding ...
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      A parallelization framework for exact knowledge hiding in transactional databases 

      Gkoulalas-Divanis, A.; Verykios, V. S. (2008)
      The hiding of sensitive knowledge, mined from transactional databases, is one of the primary goals of privacy preserving data mining. The increased storage capabilities of modern databases and the necessity for hiding ...
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