Biblio

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[ Author(Desc)] Title Type Year
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B
Bohnet, D., & Vartziotis D. (2017).  A geometric mesh smoothing algorithm related to damped oscillations. Comput Methods Appl Mech Eng. 326C,
Bohnet, D., & Vartziotis D. (2016).  Von der Symmetriegruppe des Dreiecks zur Glättung von industriellen Netzen. Die Basis der Vielfalt - 10. Tagung der DGfGG.
Bohnet, D., & Wehrlein Y. (2025).  Surrogate Model Using A U-NET-ConvLSTM Architecture For A Macroscopic Pedestrian Flow Model. ECMS 2025 Proceedings edited by Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita. 300–306.
Bohnet, D., & Vartziotis D. (2018).  Fractal Curves from Prime Trigonometric Series. Fractal Fract.. 2(2), 
Bohnet, D. (2013).  Codimension one partially hyperbolic diffeomorphisms with a uniformly compact center foliation. J. Mod. Dyn.. 7(4), 
Bohnet, D., Himpel B., & Vartziotis D. (2018).  GETOpt mesh smoothing: Putting GETMe in the framework of global optimization-based schemes. Finite Elem. Anal. Des.. 147,
Bohnet, D., & Bonatti C. (2016).  Partially hyperbolic diffeomorphisms with uniformly compact center foliation: quotient dynamics. Ergodic Theory Dyn. Sys.. 36(4), 
Bohnet, D., & Vartziotis D. (2016).  Existence of an attractor for a geometric tetrahedron transformation. Differential Geom. Appl.. 49,
Bohnet, D., & Bonatti C. (2015).  Partially hyperbolic diffeomorphisms with a uniformly compact center foliation: the quotient dynamics. Ergodic Theory and Dynamical Systems. 36, 1067–1105.
Brach, K., Sick B., & Dürr O. (2023).  Single-shot Bayesian approximation for neural networks.
Brach, K., Sick B., & Dürr O. (2020).  Single Shot MC Dropout Approximation. ICML Workshop on Uncertainty and Robustness in Deep Learning.
Burkhart, D., Hamann B., & Umlauf G. (2010).  Adaptive tetrahedral subdivision for finite element analysis. (.N., N., Ed.).Computer Graphics International, Singapore 2010. PDF icon TetraSubFEA.pdf (3.43 MB)
Burkhart, D., Hamann B., & Umlauf G. (2011).  Finite element analysis for linear elastic solids based on subdivision schemes. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop. PDF icon FEALinearElasticSolids.pdf (2.35 MB)
Burkhart, D., Hamann B., & Umlauf G. (2010).  Adaptive and feature-preserving subdivision for high-quality tetrahedral meshes. Computer Graphics Forum. 29, 117-127.PDF icon AdaptiveSubTetraMeshes.pdf (1022.53 KB)
Burkhart, D., Hamann B., & Umlauf G. (2010).  Iso-geometric analysis based on Catmull-Clark solid subdivision. Computer Graphics Forum. 29, 1575-1784.PDF icon IsoCatmullClarkSub.pdf (3.69 MB)
C
Caputo, M., Denker K., Franz M. O., Laube P., & Umlauf G. (2014).  Learning geometric primitives in point clouds. Symposium on Geometry Processing, Cardiff 2014. PDF icon Caputo et al_2014_Learning geometric primitives in point clouds.pdf (630.12 KB)
Caputo, M., Denker K., Dums B., & Umlauf G. (2012).  3d hand gesture recognition based on sensor fusion of commodity hardware. (Reiterer, H., & Deussen O., Ed.).Mensch und Computer. PDF icon GestureRecognition.pdf (378.26 KB)
Caputo, M., Denker K., Franz M. O., Laube P., & Umlauf G. (2015).  Support Vector Machines for Classification of Geometric Primitives in Point Clouds. (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. 80-95.PDF icon Caputo et al_2015_Support vector machines for classification of geometric primitives in point clouds.pdf (2.64 MB)
Casanova, R., Murina E., Haberecker M., Honcharova-Biletska H., Vrugt B., Dürr O., et al. (2018).  Automatic classification of non-small cell lung cancer histologic sub-types by deep learning. VIRCHOWS ARCHIV. 108-108.
Cieliebak, M., Dürr O., & Uzdilli F. (2014).  Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools.. Language Resources and Evaluation Conference (LREC). 3100–3104.
Cieliebak, M., Dürr O., & Uzdilli F. (2013).  Potential and Limitations of Commercial Sentiment Detection Tools.. ESSEM@ AI* IA. 47–58.
Constantiniu, A., Steinmann P., Bobach T., Farin G., & Umlauf G. (2008).  The adaptive Delaunay tesselation: A neighborhood covering meshing technique. Computational Mechanics. 42, 655-669.PDF icon AdaptDelTess.pdf (1.33 MB)
D
Dahmen, H.-J., Franz M. O., & Krapp H. G. (2001).  Extracting egomotion from optic flow: limits of accuracy and neural matched filters. (Zanker, J. M., & Zeil J., Ed.).{Motion Vision: Computational, Neural and Ecological Constraints}. 143-168.PDF icon Dahmen, Franz, Krapp_2001_Extracting egomotion from optic flow- limits of accuracy and neural matched filters.pdf (223.04 KB)
Danhof, M., Schneider T., Laube P., & Umlauf G. (2015).  A Virtual-Reality 3d-Laser-Scan Simulation. BW-CAR| SINCOM. 68.
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)

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