% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@MISC{Strube:1038646,
      author       = {Strube, Alexandre and Benassou, Sabrina and Kasravi, Javad
                      and Dickscheid, Timo and Schiffer, Christian},
      title        = {{D}eep {L}earning for {N}euroscience},
      reportid     = {FZJ-2025-01617},
      year         = {2024},
      abstract     = {Machine Learning – in particular deep learning – has
                      become an indispensable tool for analyzing large
                      neuroscience datasets. The Helmholtz AI team at Jülich is
                      closely connected to these developments and supports
                      research activities at the intersection of AI,
                      high-performance computing (HPC) and neuroscience. Many of
                      the methods and solutions are not limited to neuroscience
                      and medical applications, but can be transferred to
                      different tasks and scientific domains.This tutorial we will
                      give an overview of state-of-the-art deep learning methods
                      in the context of biomedical image analysis and show
                      concrete examples in INM where deep learning already
                      supports neuroscientists in analyzing their data. The second
                      part of this tutorial will offer a hands-on course on how to
                      bring deep learning pipelines on JSC’s HPC systems.},
      month         = {Nov},
      date          = {2024-11-19},
      organization  = {Forschungszentrum Jülich, Jülich
                       (Germany), 19 Nov 2024 - 19 Nov 2024},
      subtyp        = {Other},
      cin          = {JSC / INM-1},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)INM-1-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / 5251 - Multilevel Brain
                      Organization and Variability (POF4-525) / Helmholtz AI
                      Consultant Team FB Information (E54.303.11)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(DE-HGF)POF4-5251 /
                      G:(DE-Juel-1)E54.303.11},
      typ          = {PUB:(DE-HGF)17},
      url          = {https://juser.fz-juelich.de/record/1038646},
}