Biblio

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[ Author(Asc)] Title Type Year
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D
Dürr, O. (2003).  Theoretical Studies of Relaxation and Ionic Transport in Polymers.
Dürr, O. (1998).  Monte-carlo-simulationen zu polymeren ionenleitern.
Dürr, O., & Sick B. (2016).  Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks. Journal of biomolecular screening. 21, 998–1003.
Dürr, O., Fan P-Y., & Yin Z-X. (2023).  Bayesian Calibration of MEMS Accelerometers. IEEE Sensors Journal.
Dürr, O., & Brandenburg A. (2012).  Using Community Structure for Complex Network Layout. arXiv preprint arXiv:1207.6282.
Dürr, O., Sick B., & Murina E. (2020).  Probabilistic deep learning: With python, keras and tensorflow probability.
Dürr, O., Uzdilli F., & Cieliebak M. (2014).  JOINT\_FORCES: Unite Competing Sentiment Classifiers with Random Forest.. SemEval@ COLING. 366–369.
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.
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.PDF icon 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.
Dürr, O., Sick B., & Murina E. (2020).  Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability.
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.
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.
Dürr, O., & Dieterich W. (2007).  Glassy and Polymeric Ionic Conductors: Statistical Modeling and Monte Carlo Simulations. Superionic Conductor Physics. 1, 77–80.
Dold, D., Arpogaus M., & Dürr O. (2023).  Deep probabilistic modelling for energy forecasting. PDF icon Poster_Deep probabilistic modelling for energy forecasting TTT.pdf (839.27 KB)
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.
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.
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.
Denker, K., & Umlauf G. (2011).  An accurate real-time multi-camera matching on the GPU for 3d reconstruction. Journal of WSCG. 19, 9-16.PDF icon RealTimeMultiCamera.pdf (770.39 KB)
Denker, K., Lehner B., & Umlauf G. (2011).  Real-time triangulation of point streams. Engineering with Computers. 27, 67-80.PDF icon RTTriangulationPointStreams.pdf (1.05 MB)
Denker, K., Hagel D., Raible J., Umlauf G., & Hamann B. (2013).  On-line reconstruction of CAD geometry. International Conference on 3d Vision. PDF icon OnlineReconstruction.pdf (392.38 KB)
Denker, K., Lehner B., & Umlauf G. (2008).  Online triangulation of laser-scan data. (Garimella, R., Ed.).Proceedings of the 17th International Meshing Roundtable 2008. PDF icon OnlineTriang.pdf (8.39 MB)
Denker, K., Hamann B., & Umlauf G. (2015).  On-line CAD Reconstruction with Accumulated Means of Local Geometric Properties. (Boissonnat, J-D., Cohen A., Gibaru O., Gout C., Lyche T., Mazure M-L., et al., Ed.).Curves and Surfaces, 8th International Conference, Paris 2014. 181-201.PDF icon OnlineCADReconst.pdf (3.18 MB)
Denker, K., & Umlauf G. (2011).  Survey on benchmarks for a GPU based multi camera stereo matching algorithm. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop. PDF icon BenchmarkStereoMatching.pdf (3.63 MB)
Danhof, M., Schneider T., Laube P., & Umlauf G. (2015).  A Virtual-Reality 3d-Laser-Scan Simulation. BW-CAR| SINCOM. 68.

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