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@ARTICLE{Segadlo:912197,
      author       = {Segadlo, Kai and Epping, Bastian and van Meegen, Alexander
                      and Dahmen, David and Krämer, Michael and Helias, Moritz},
      title        = {{U}nified field theoretical approach to deep and recurrent
                      neuronal networks},
      journal      = {Journal of statistical mechanics: theory and experiment},
      volume       = {2022},
      number       = {10},
      issn         = {1742-5468},
      address      = {Bristol},
      publisher    = {IOP Publ.},
      reportid     = {FZJ-2022-05400},
      pages        = {103401},
      year         = {2022},
      cin          = {INM-6 / IAS-6 / INM-10},
      ddc          = {530},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {5232 - Computational Principles (POF4-523) / HBP SGA3 -
                      Human Brain Project Specific Grant Agreement 3 (945539) /
                      ACA - Advanced Computing Architectures (SO-092) /
                      RenormalizedFlows - Transparent Deep Learning with
                      Renormalized Flows (BMBF-01IS19077A) / SDS005 - Towards an
                      integrated data science of complex natural systems
                      (PF-JARA-SDS005)},
      pid          = {G:(DE-HGF)POF4-5232 / G:(EU-Grant)945539 / G:(DE-HGF)SO-092
                      / G:(DE-Juel-1)BMBF-01IS19077A /
                      G:(DE-Juel-1)PF-JARA-SDS005},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000865596900001},
      doi          = {10.1088/1742-5468/ac8e57},
      url          = {https://juser.fz-juelich.de/record/912197},
}