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Dr. Andreas Ruttor

Lupe
Lupe

Scientific Assistant
Office: MAR 4.019
Phone: +49 30 314-23938
E-Mail: andreas.ruttor <AT> tu-berlin.de


Consulting hour according to agreement.

Curriculum vitae

Andreas Ruttor
Born 1977

Academic Career
Period
Occupation
since 2007
Post-Doc Researcher at TU Berlin, Artificial Intelligence Group

2007
Ph. D. in Physics, Universität Würzburg
2003-2007
Research Assistant at Universität Würzburg, Statistical Physics Group

2003
Master in Physics, Universität Würzburg

Research Fields

  • Stochastic dynamical systems (exact and approximate inference, model selection)
  • Statistical learning theory (Gaussian processes, neural networks)
  • Statistical physics of complex systems
  • Applications: Systems biology, data analysis, cryptography

Publications

Philipp Batz and Andreas Ruttor and Manfred Opper (2016). Variational estimation of the drift for stochastic differential equations from the empirical density. Journal of Statistical Mechanics: Theory and Experiment, 083404.



Andreas Ruttor and Philipp Batz and Manfred Opper (2013). Approximate Gaussian process inference for the drift of stochastic differential equations. Advances in Neural Information Processing Systems, 2040-2048.


Sven Wiethölder and Andreas Ruttor and Uwe Bergemann and Manfred Opper and Adam Wolisz (2013). DARA: Estimating the Behavior of Data Rate Adaptation Algorithms in WLAN Hotspots.


Sven Wiethölter and Andreas Ruttor and Uwe Bergemann and Manfred Opper and Adam Wolisz (2013). DARA: Estimating the Behavior of Data Rate Adaptation Algorithms in WLAN Hotspots.


Florian Stimberg and Manfred Opper and Andreas Ruttor (2012). Bayesian Inference for Change Points in Dynamical Systems with Reusable States—a Chinese Restaurant Process Approach. Proceedings of the International Conference on Artificial Intelligence and Statistics


Luís Francisco Seoane Iglesias and Andreas Ruttor (2012). Successful attack on permutation-parity-machine-based neural cryptography. Physical Review E, 025101(R).


Florian Stimberg and Andreas Ruttor and Manfred Opper (2011). Bayesian Inference for Models of Transcriptional Regulation Using Markov Chain Monte Carlo Sampling. Proceedings of the 8th International Workshop on Computational Systems Biology (WCSB). Tampere University of Technology, Tampere, Finland, 169–172.


Florian Stimberg and Manfred Opper and Guido Sanguinetti and Andreas Ruttor (2011). Inference in continuous-time change-point models. Advances in Neural Information Processing Systems 24, 2717–2725.


Andreas Ruttor and Guido Sanguinetti and Manfred Opper (2010). Approximate inference for stochastic reaction processes. Learning and Inference in Computational Systems Biology. MIT Press, 189-205.


Andreas Ruttor and Manfred Opper (2010). Approximate parameter inference in a stochastic reaction-diffusion model. Proceedings of The Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010. JMLR, 669-676.


Manfred Opper and Andreas Ruttor and Guido Sanguinetti (2010). Approximate inference in continuous time Gaussian-Jump processes. Advances in Neural Information Processing Systems 23, 1831–1839.


Andreas Ruttor and Florian Stimberg and Manfred Opper (2010). Comparing diffusion and weak noise approximations for inference in reaction models. Proceedings of the Fourth International Workshop on Machine Learning in Systems Biology (October 15-16, 2010, Edinburgh, UK), 149–152.


Florian Stimberg and Andreas Ruttor and Manfred Opper (2010). MCMC for continuous time switching models. NIPS Workshop on Monte Carlo Methods for Modern Applications (December 10, 2010, Whistler, Canada)


Andreas Ruttor and Guido Sanguinetti and Manfred Opper (2009). Approximate inference for stochastic reaction processes. Learning and Inference in Computational Systems Biology. The MIT Press, 189–205.


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Postal Address

TU Berlin
Fakultät IV
Elektrotechnik und Informatik
sec. MAR 4-2
Marchstrasse 23
D-10587 Berlin