Biblio

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2023
Arpogaus, M., Voss M., Sick B., Nigge-Uricher M., & Dürr O. (2023).  Short-term density forecasting of low-voltage load using Bernstein-polynomial normalizing flows. IEEE Transactions on Smart Grid.
2021
Arpogaus, M., Voß M., Sick B., Nigge-Uricher M., & Dürr O. (2021).  Probabilistic Short-Term Low-Voltage Load Forecasting using Bernstein-Polynomial Normalizing Flows. ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual. PDF icon Arpogaus2021_Probabilistic_Forecasting.pdf (427.35 KB)
Arpogaus, M., Voß M., Sick B., Nigge-Uricher M., & Dürr O. (2021).  Probabilistic short-term low-voltage load forecasting using bernstein-polynomial normalizing flows. ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual.
2019
Schambach, M-P., von der Nüll S., & Schall M. (2019).  Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms. ICDAR-OST: The 2nd International Workshop on Open Services and Tools for Document Analysis. PDF icon Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.pdf (776.45 KB)
2018
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.
Bohnet, D., & Vartziotis D. (2018).  Fractal Curves from Prime Trigonometric Series. Fractal Fract.. 2(2), 
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,
2017
Bohnet, D., & Vartziotis D. (2017).  A geometric mesh smoothing algorithm related to damped oscillations. Comput Methods Appl Mech Eng. 326C,
2016
Bohnet, D., & Vartziotis D. (2016).  Existence of an attractor for a geometric tetrahedron transformation. Differential Geom. Appl.. 49,
Bohnet, D., & Vartziotis D. (2016).  Von der Symmetriegruppe des Dreiecks zur Glättung von industriellen Netzen. Die Basis der Vielfalt - 10. Tagung der DGfGG.
2006
Bobach, T., Bertram M., & Umlauf G. (2006).  Comparison of Voronoi based scatterd data interpolation schemes. (Villanueva, J.J., Ed.).Proceedings of the Internationl Conference on Visualization, Imaging and Image Processing. PDF icon VoronoiInterp.pdf (4.63 MB)