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Press Coverage

DateTitle
Fall 2017InSiDE - Helmholtz Analytics Framework

Presentations

DateTitle
2018-06-28  Helmholtz Analytics Framework (PDF, 2 MB) , Vancouver
2017-06-12  Project Proposal Presentation, Berlin (PDF, 642 kB)

Events

DateTitle
2019-05-13All Hands Meeting, Heidelberg
2019-03-14 - 2019-03-152nd Data Analysis Methods (DAMe) Workshop, Hamburg
2018-08-14All Hands Meeting, Cologne
2018-03-22 - 2018-03-23Data Analysis Methods (DAMe) Workshop, Karlsruhe
2017-10-09 - 2017-10-10Project Kick-Off Meeting, Jülich

Publications

  • R. Gutzen, M. von Papen, G. Trensch, P. Quaglio, S. Grün and M. Denker (2018) Reproducible Neural Network Simulations: Statistical Methods for Model Validation on the Level of Network Activity Data. Front. Neuroinform. 12:90. doi:10.3389/fninf.2018.00090 https://www.frontiersin.org/articles/10.3389/fninf.2018.00090/abstract
  • J. Schroeter, M. Braun, R. Ruhnke, P. Braesicke (2018) Interactive versus prescribed ozon in the ICON-ART climate model: how is the spectrum of variability changing? Poster A41I-3081 presented at 2018 Fall Meeting, AGU, Washington, D.C., 10-14 Dec.,  Interactive versus prescribed ozone in the ICON-ART climate model: how is the spectrum of variability changing? (PDF, 5 MB)
  • M. Weiel, I. Reinartz, A. Schug (2019) Rapid interpretation of small-angle X-ray scattering data. PLOS Computational Biology 15(3): e1006900. https://doi.org/10.1371/journal.pcbi.1006900
  • K. Krajsek, C. Comito, M. Götz, B. Hagemeier, Ph. Knechtges, M. Siggel, The Helmholtz Analytics Toolkit (HeAT) - A Scientific Big Data Library for HPC, Extreme Data – Demands, Technologies, and Services, Jülich, 18.-19. Sept. 2018, IAS Series Vol. 40, 2019, 57-60: http://hdl.handle.net/2128/22029.
  • Karunakar R. Pothula, Daryna Smyrnova , Gunnar F. Schröder, Clustering cryo-EM images of helical protein polymers for helical reconstructions, Ultramicroscopy (2019) 203:132-138, https://doi.org/10.1016/j.ultramic.2018.12.009.
  • M. Götz and H. Anzt, Machine Learning-Aided Numerical Linear Algebra: Convolutional Neural Networks for the Efficient Preconditioner Generation, in 2018 IEEE/ACM 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (scalA), 2018, pp. 49–56.
  • M. Bockwoldt, D. Houry, M. Niere, T.I. Gossmann, I. Reinartz, A. Schug, M. Ziegler, and I. Heiland. Identifying evolutionary and kinetic drivers of NAD-dependent signaling. Proc. Natl. Acad. Sci. U.S.A.  (accepted)
  • O. Taubert, I. Reinartz, H. Meyerhenke, and A. Schug. diSTruct v1.0: Generating Biomolecular Structures from Distance Constraints. Bioinformatics (accepted)
  • D. Todt. Untersuchung räumlicher Muster in meteorologischen Modellen für die Ensemble-Kalibrierung mittels tiefer neuronaler Netze [Engl.: "Examination of Spatial Patterns in Meteorological Models for Ensemble Calibration Using Neural Networks"]. Bachelor thesis, 2019.
  • Julian Moosmann, Florian Wieland, Berit Zeller-Plumhoff, Silvia Galli, Diana Krüger, Alexey Ershov, Silke Lautner, Julian Sartori, Mason Dean, Sebastian Köhring, Hilmar Burmester, Thomas Dose, Niccoló Peruzzi, Ann Wennerberg, Regine Willumeit-Römer, Fabian Wilde, Philipp Heuser, Jörg U. Hammel, Felix Beckmann (2019) A load frame for in situ tomography at PETRA III. Proceedings Volume 11113, Developments in X-Ray Tomography XII; 1111318 (2019) https://doi.org/10.1117/12.2530445 Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

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