Dieterich, W., Dürr O., Pendzig P., & Nitzan A. (1999).  Stochastic modelling of ion diffusion in complex systems. Anomalous Diffusion From Basics to Applications. 175–185.

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Dieterich, W., Dürr O., Pendzig P., Bunde A., & Nitzan A. (1999).  Percolation concepts in solid state ionics. Physica A: Statistical Mechanics and its Applications. 266, 229–237.

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Distler, H. K., van Veen H. A. H. C., Braun S. J., Heinz W., Franz M. O., & Bülthoff H. H. (1998).  Navigation in real and virtual environments: judging orientation and distance in a large-scale landscape. (Goebel, M., Lang U., Landauer J., & Walper M., Ed.).{Virtual Environment 98: Proc. of the Eurographics Workshop 1998}. 124 – 133.

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Dold, D., Arpogaus M., & Dürr O. (2023).  Deep probabilistic modelling for energy forecasting.

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Poster_Deep probabilistic modelling for energy forecasting TTT.pdf (839.27 KB)

Dürr, O., Dieterich W., & Nitzan A. (2001).  Charge Transport in Polymer Ion Conductors: a Monte Carlo Study. arXiv preprint cond-mat/0106197.

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Dürr, O., Dieterich W., & Nitzan A. (2002).  Diffusion in polymer electrolytes and the dynamic percolation model. Solid state ionics. 149, 125–130.

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Dürr, O., Duval F., Nichols A., Lang P., Brodte A., Heyse S., et al. (2007).  Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay. Journal of biomolecular screening. 12, 1042–1049.

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Dürr, O., Pendzig P., Dieterich W., & Nitzan A. (2001).  Model studies of diffusion in glassy and polymer ion conductors. arXiv preprint cond-mat/0106196.

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Dürr, O. (2003).  Theoretical Studies of Relaxation and Ionic Transport in Polymers.

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Dürr, O. (1998).  Monte-carlo-simulationen zu polymeren ionenleitern.

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Dürr, O., & Sick B. (2016).  Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks. Journal of biomolecular screening. 21, 998–1003.

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Dürr, O., Fan P-Y., & Yin Z-X. (2023).  Bayesian Calibration of MEMS Accelerometers. IEEE Sensors Journal.

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Dürr, O., & Brandenburg A. (2012).  Using Community Structure for Complex Network Layout. arXiv preprint arXiv:1207.6282.

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Dürr, O., Sick B., & Murina E. (2020).  Probabilistic deep learning: With python, keras and tensorflow probability.

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Dürr, O., Uzdilli F., & Cieliebak M. (2014).  JOINT\_FORCES: Unite Competing Sentiment Classifiers with Random Forest.. SemEval@ COLING. 366–369.

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Dürr, O., Dieterich W., & Nitzan A. (2004).  Coupled ion and network dynamics in polymer electrolytes: Monte Carlo study of a lattice model. The Journal of chemical physics. 121, 12732–12739.

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Dürr, O., Murina E., Siegismund D., Tolkachev V., Steigele S., & Sick B. (2018).  Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes. Assay and drug development technologies. 16, 343–349.

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adt.2018.859.pdf (711.06 KB)

Dürr, O., Dieterich W., Maas P., & Nitzan A. (2002).  Effective medium theory of conduction in stretched polymer electrolytes. arXiv preprint cond-mat/0202165.

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Dürr, O., Sick B., & Murina E. (2020).  Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability.

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Dürr, O., Volz T., Dieterich W., & Nitzan A. (2002).  Dynamic percolation theory for particle diffusion in a polymer network. The Journal of chemical physics. 117, 441–447.

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Dürr, O., Pauchard Y., Browarnik D., Axthelm R., & Loeser M. (2015).  Deep Learning on a Raspberry Pi for Real Time Face Recognition.. Eurographics (Posters). 11–12.

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Dürr, O., & Dieterich W. (2007).  Glassy and Polymeric Ionic Conductors: Statistical Modeling and Monte Carlo Simulations. Superionic Conductor Physics. 1, 77–80.

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Franz, M. O., Schölkopf B., Mallot H. A., Bülthoff H. H., & Zell A. (1998).  Navigation mit Schnappschüssen.. (Levi, P., Ahlers R.-J., May F., & Schanz M., Ed.).{Mustererkennung 1998. Proc. of the 20th DAGM-Symposium}. 412-428.

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Franz et al._1998_Navigation mit Schnappschüssen.pdf (300.5 KB)

Franz, M. O., & Krapp H. G. (2000).  Wide-field, motion-sensitive neurons and matched filters for optic flow fields. Biol. Cybern.. 83, 185 – 197.

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Franz, Krapp_2000_Wide-field, motion-sensitive neurons and matched filters for optic flow fields.pdf (261.7 KB)

Franz, M. O., Schölkopf B., Mallot H. A., & Bülthoff H. H. (1998).  Learning view graphs for robot navigation. Autonomous Robots. 5, 111 – 125.

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Franz et al._1998_Learning View Graphs for Robot Navigation.pdf (1.26 MB)