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  • H. G. Matthies, E. Zander, B. V. Rosić, A. Litvinenko, O. Pajonk, Inverse Problems in a Bayesian Setting, Chapter in the book Computational Methods for Solids and Fluids, edited by Adnan Ibrahimbegovic, Springer, 2016
Inverse Problems in a Bayesian Setting
  • Hakim Ghazzai, Elias Yaacoub, Mohamed-Slim Alouini, Adnan Abu Dayya​, "Smart grid energy procurement for green LTE cellular networks", Green Networking and Communications: ICT for Sustainability, 2013
LTE networks, smart grid
  • A.

    Litvinenko and H. G. Matthies, Numerical Methods for Uncertainty Quantification and Bayesian update in Aerodynamics. Chapter in the book Management and Minimisation of Uncertainties and Errors in Numerical Aerodynamics, pp. 267-283, Editors: B. Eisfeld, H. Barnewitz, W. Fritz, F. Thiele, Springer, 2013

Numerical Methods for Uncertainty Quantification and Bayesian update in Aerodynamics
  • Q. Zhu, H. Tembine, and T. Basar. Hybrid learning in stochastic games and its applications in network security. In F. L. Lewis, D. Liu (Eds.) Reinforcement Learning and Approximate Dynamic Programming for Feedback Control, Series on Computational Intelligence, IEEE Press/Wiley, 2013, chapter 14, pp. 305-329
Strategic Learning, Hybrid systems, Game Theory, Network Security
  • Hoel, Håkon; von Schwerin, Erik; Szepessy, Anders; Tempone, Raúl Adaptive multilevel Monte Carlo simulation. Numerical analysis of multiscale computations, 217–234, Lect. Notes Comput. Sci. Eng., 82, Springer, Heidelberg, 2012.

Computational finance, Monte Carlo, multilevel, adaptivity, weak approximation, error control, Euler–Maruyama method, a posteriori error estimates, backward dual functions, adjoints
  • H. Tembine, P. Vilanova, and M. Debbah. Noisy mean field game model for malware propagation in opportunistic networks. In Rahul Jain and Rajgopal Kannan, editors, Game Theory for Networks, volume 75 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pages 459-474. Springer Berlin Heidelberg, 2012. 
Mean field games, opportunistic networks.