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@MISC{Fischer:1052972,
      author       = {Fischer, Kirsten and Dahmen, David and Helias, Moritz},
      title        = {{F}ield theory for optimal signal propagation in
                      {R}es{N}ets},
      reportid     = {FZJ-2026-01322},
      year         = {2025},
      abstract     = {This repository contains the code accompanying the paper:
                      Fischer, K., Dahmen, D., Helias, M. (2023). Field theory for
                      optimal signal propagation in ResNets (arXiv:2305.07715).
                      For any questions, please contact Kirsten Fischer
                      (ki.fischer@fz-juelich.de).},
      keywords     = {Field theory (Other) / Residual networks (Other) / Machine
                      Learning (Other)},
      cin          = {IAS-6},
      cid          = {I:(DE-Juel1)IAS-6-20130828},
      pnm          = {5231 - Neuroscientific Foundations (POF4-523) / 5232 -
                      Computational Principles (POF4-523) / RenormalizedFlows -
                      Transparent Deep Learning with Renormalized Flows
                      (BMBF-01IS19077A) / GRK 2416 - GRK 2416:
                      MultiSenses-MultiScales: Neue Ansätze zur Aufklärung
                      neuronaler multisensorischer Integration (368482240) / ACA -
                      Advanced Computing Architectures (SO-092) / Brain-Scale
                      Simulations $(jinb33_20220812)$ / DFG project
                      G:(GEPRIS)491111487 - Open-Access-Publikationskosten / 2025
                      - 2027 / Forschungszentrum Jülich (OAPKFZJ) (491111487)},
      pid          = {G:(DE-HGF)POF4-5231 / G:(DE-HGF)POF4-5232 /
                      G:(DE-Juel-1)BMBF-01IS19077A / G:(GEPRIS)368482240 /
                      G:(DE-HGF)SO-092 / $G:(DE-Juel1)jinb33_20220812$ /
                      G:(GEPRIS)491111487},
      typ          = {PUB:(DE-HGF)33},
      doi          = {10.5281/ZENODO.17395886},
      url          = {https://juser.fz-juelich.de/record/1052972},
}