The following publications have been created with bibtex2html from a bibtext-file exported from my google scholar site. See also my researchgate site.

[1] Dürr, O., and Sick, B. Single-cell phenotype classification using deep convolutional neural networks. Journal of biomolecular screening 21, 9 (2016), 998-1003. [ bib ]
[2] Lukic, Y., Vogt, C., Dürr, O., and Stadelmann, T. Speaker identification and clustering using convolution neural networks. In IEEE International workshop on Machine Learning for Signal Processing (2016). [ bib ]
[3] Dürr, O., Pauchard, Y., Browarnik, D., Axthelm, R., and Loeser, M. Deep learning on a raspberry pi for real time face recognition. In Eurographics (Posters) (2015), pp. 11-12. [ bib ]
[4] Franzini, A., Baty, F., Macovei, I. I., Dürr, O., Droege, C., Betticher, D., Grigoriu, B. D., Klingbiel, D., Zappa, F., and Brutsche, M. H. Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced nonsquamous non-small cell lung cancer patients (sakk 19/05 trial). Clinical Cancer Research 21, 23 (2015), 5253-5263. [ bib ]
[5] Franzini, A., Dürr, O., Baty, F., and Brutsche, M. Tumor-associated stromal gene expression signatures predict therapeutic response to erlotinib/bevacizumab in non-small cell lung cancer (nsclc). European Respiratory Journal 44, Suppl 58 (2014), P821. [ bib ]
[6] Cieliebak, M., Dürr, O., and Uzdilli, F. Meta-classifiers easily improve commercial sentiment detection tools. In Language Resources and Evaluation Conference (LREC) (2014), pp. 3100-3104. [ bib ]
[7] Dürr, O., Uzdilli, F., and Cieliebak, M. Joint_forces: Unite competing sentiment classifiers with random forest. In SemEval 2014-Proceedings of the 8th International Workshop on Semantic Evaluation (2014), pp. 366-369. [ bib ]
[8] Cieliebak, M., Dürr, O., and Uzdilli, F. Potential and limitations of commercial sentiment detection tools. In ESSEM@ AI* IA (2013), Citeseer, pp. 47-58. [ bib ]
[9] Dürr, O., and Brandenburg, A. Using community structure for complex network layout. arXiv preprint arXiv:1207.6282 (2012). [ bib ]
[10] Dürr, O., Duval, F., Nichols, A., Lang, P., Brodte, A., Heyse, S., and Besson, D. Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay. Journal of biomolecular screening 12, 8 (2007), 1042-1049. [ bib ]
[11] Dürr, O., and Dieterich, W. Glassy and polymeric ionic conductors: Statistical modeling and monte carlo simulations. In Superionic Conductor Physics (2007), vol. 1, pp. 77-80. [ bib ]
[12] Heyse, S., Brodte, A., Bruttger, O., Duerr, O., Freeman, T., Jung, T., Lindemann, M., Ottl, J., and Rinn, B. Quantifying bioactivity on a large scale: quality assurance and analysis of multiparametric ultra-hts data. Journal of the Association for Laboratory Automation 10, 4 (2005), 207-212. [ bib ]
[13] Rinn, B., Heyse, S., Brodte, A., Bruttger, O., Duerr, O., Freeman, T., Jung, T., Lindemann, M., and Ottl, J. Journal of the association for laboratory. [ bib ]
[14] Dürr, O., Dieterich, W., and Nitzan, A. Coupled ion and network dynamics in polymer electrolytes: Monte carlo study of a lattice model. The Journal of chemical physics 121, 24 (2004), 12732-12739. [ bib ]
[15] Dürr, O. Theoretical Studies of Relaxation and Ionic Transport in Polymers. PhD thesis, 2003. [ bib ]
[16] Dürr, O., Volz, T., Dieterich, W., and Nitzan, A. Dynamic percolation theory for particle diffusion in a polymer network. The Journal of chemical physics 117, 1 (2002), 441-447. [ bib ]
[17] Dürr, O., Dieterich, W., Maass, P., and Nitzan, A. Effective medium theory of conduction in stretched polymer electrolytes. The Journal of Physical Chemistry B 106, 24 (2002), 6149-6155. [ bib ]
[18] Dürr, O., Dieterich, W., and Nitzan, A. Diffusion in polymer electrolytes and the dynamic percolation model. Solid state ionics 149, 1 (2002), 125-130. [ bib ]
[19] Dürr, O., Nitzan, A., and Dieterich, W. Charge transport in polymer ion conductors. Comput. Syst. Sci. 177, cond-mat/0106197 (2001), 288-292. [ bib ]
[20] Oliver, D., Frisch, H., and Dieterich, W. Melt viscosities of lattice polymers using a kramers potential treatment. J. Chem. Phys. 115 (2001), 9042-9045. [ bib ]
[21] Dieterich, W., Dürr, O., Pendzig, P., Bunde, A., and Nitzan, A. Percolation concepts in solid state ionics. Physica A: Statistical Mechanics and its Applications 266, 1 (1999), 229-237. [ bib ]
[22] Dieterich, W., Dürr, O., Pendzig, P., and Nitzan, A. Stochastic modelling of ion diffusion in complex systems. In Anomalous Diffusion From Basics to Applications. Springer, 1999, pp. 175-185. [ bib ]
[23] Dürr, O. Monte-carlo-simulationen zu polymeren ionenleitern. [ bib ]

This file was generated by bibtex2html 1.96.