.. List of References

******************
List of References
******************

.. [Bourinet2009] J.-M. Bourinet, C. Mattrand, and V Dubourg. A review of recent features and improvements added to FERUM software. In Proc. of the 10th International Conference on Structural Safety and Reliability (ICOSSAR’09), Osaka, Japan, 2009.

.. [Bourinet2010] J.-M. Bourinet. FERUM 4.1 User’s Guide, 2010.

.. [DerKiureghian2006] A. Der Kiureghian, T. Haukaas, and K. Fujimura. Structural reliability software at the University of California, Berkeley. Structural Safety, 28(1-2):44–67, 2006.

.. [Hackl2013] J. Hackl. Generic Framework for Stochastic Modeling of Reinforced Concrete Deterioration Caused by Corrosion. Master’s thesis, Norwegian University of Science and Technology, Trondheim, Norway, 2013.

.. [Langtangen2009] Hans Petter Langtangen. Python Scripting for Computational Science. Springer-Verlag, 2009.

.. [Lutz2007] M. Lutz. Learning Python. O’Reilly, 2007.

.. [Jensen2007] Jensen, Finn V. and Thomas D. Nielsen (2007). Bayesian Networks and Decision Graphs. second edition. Information Science and Statistic. Springer Publishing Company, Incorporated. isbn: 9780387682815.

.. [Jordan2007] Jordan, Michael I. (2007). An Introduction to Graphical Models. In preperation.

.. [Pearl1988] Pearl, Judea (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Representation and Reasoning Series. San Francisco: Morgan Kaufman Publischer. isbn: 9781558604797.

.. [Pearl2000] Pearl, Judea (2000). Causality: Models, Reasoning, and Inference. Cambridge, Massachusetts: Cambridge University Press. isbn: 9780521773621.

.. [Pernkopf2013] Pernkopf, Franz, Robert Peharz, and Sebastian Tschiatschek (2013). "Introduction to Probabilistic Graphical Models". In: E-Reference Signal Processin. In preperation. Elsevier.

.. [Stephenson2000] Stephenson, Todd A. (Feb. 2000). "An Introduction to Bayesian Network Theory and Usage"". In: IDIAP Reseach Report 00-03.

.. [Koller2009] Koller, Daphne and Nir Friedman (2009). Probabilistic Graphical Models: Principles and Techniques. first edition. Massachusetts: MIT Press.

.. [Murphy2012] Murphy, Kevin P. (2012). Machine Learning: A Probabilistic Perspective. first edition. Adaptive computation and machine learning series. Cambridge, Massachusetts: MIT Press. isbn: 9780262018029.