Biblio

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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)
Dieterich, W., Dürr O., Pendzig P., & Nitzan A. (2007).  Stochastic modelling of ion diffusion in complex systems. Anomalous Diffusion From Basics to Applications. 175–185.
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.
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.
Dold, D., Kobialka J., Palm N., Sommer E., Rügamer D., & Dürr O. (2025).  Paths and Ambient Spaces in Neural Loss Landscapes. (Li, Y., Mandt S., Agrawal S., & Khan E., Ed.).Proceedings of The 28th International Conference on Artificial Intelligence and Statistics. 10–18.
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)
Dold, D., Ruegamer D., Sick B., & Dürr O. (2024).  Bayesian Semi-structured Subspace Inference. (Dasgupta, S., Mandt S., & Li Y., Ed.).Proceedings of The 27th International Conference on Artificial Intelligence and Statistics. 1819–1827.
Duerr, O., & Heyse S. (2006).  Multivariate analysis of siRNA/high content screening data.
Dürr, O., Dieterich W., & Nitzan A. (2001).  Charge Transport in Polymer Ion Conductors: a Monte Carlo Study. arXiv preprint cond-mat/0106197.
Dürr, O., Dieterich W., & Nitzan A. (2002).  Diffusion in polymer electrolytes and the dynamic percolation model. Solid state ionics. 149, 125–130.
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.
Dürr, O., Pendzig P., Dieterich W., & Nitzan A. (2001).  Model studies of diffusion in glassy and polymer ion conductors. arXiv preprint cond-mat/0106196.
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.

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