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@INPROCEEDINGS{Wasmer:1022478,
      author       = {Wasmer, Johannes and Rüssmann, Philipp and Assent, Ira and
                      Blügel, Stefan},
      title        = {{M}achine {L}earning {E}mulators for {F}irst-{P}rinciples
                      {S}imulations of {Q}uantum {M}aterials},
      school       = {RWTH Aachen University},
      reportid     = {FZJ-2024-01472},
      year         = {2023},
      abstract     = {Poster about Johannes Wasmer's PhD project, presented at
                      the HDS-LEE Midterm Evaluation in February 2023.},
      month         = {Feb},
      date          = {2023-02-13},
      organization  = {HDS-LEE internal event, Jülich
                       (Germany), 13 Feb 2023 - 15 Feb 2023},
      subtyp        = {Other},
      keywords     = {density functional theory (Other) / machine learning
                      (Other) / quantum materials (Other) / topological insulators
                      (Other) / scientific workflows (Other) / AiiDA (Other) /
                      magnetism (Other) / materials database (Other) / material
                      defects (Other)},
      cin          = {IAS-1 / PGI-1},
      cid          = {I:(DE-Juel1)IAS-1-20090406 / I:(DE-Juel1)PGI-1-20110106},
      pnm          = {5211 - Topological Matter (POF4-521) / HDS LEE - Helmholtz
                      School for Data Science in Life, Earth and Energy (HDS LEE)
                      (HDS-LEE-20190612) / AIDAS - Joint Virtual Laboratory for
                      AI, Data Analytics and Scalable Simulation
                      $(aidas_20200731)$},
      pid          = {G:(DE-HGF)POF4-5211 / G:(DE-Juel1)HDS-LEE-20190612 /
                      $G:(DE-Juel-1)aidas_20200731$},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.5281/ZENODO.10441576},
      url          = {https://juser.fz-juelich.de/record/1022478},
}