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@ARTICLE{Jadebeck:885878,
      author       = {Jadebeck, Johann F and Theorell, Axel and Leweke, Samuel
                      and Nöh, Katharina},
      title        = {{HOPS}: high-performance library for (non-)uniform sampling
                      of convex-constrained models},
      journal      = {Bioinformatics},
      volume       = {37},
      number       = {12},
      issn         = {1460-2059},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {FZJ-2020-04154},
      pages        = {1776-1777},
      year         = {2020},
      abstract     = {The C++ library Highly Optimized Polytope Sampling (HOPS)
                      provides implementations of efficient and scalable
                      algorithms for sampling convex-constrained models that are
                      equipped with arbitrary target functions. For uniform
                      sampling, substantial performance gains were achieved
                      compared to the state-of-the-art. The ease of integration
                      and utility of non-uniform sampling is showcased in a
                      Bayesian inference setting, demonstrating how HOPS
                      interoperates with third-party software.},
      cin          = {IBG-1},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IBG-1-20101118},
      pnm          = {583 - Innovative Synergisms (POF3-583)},
      pid          = {G:(DE-HGF)POF3-583},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {33045081},
      UT           = {WOS:000693171600023},
      doi          = {10.1093/bioinformatics/btaa872},
      url          = {https://juser.fz-juelich.de/record/885878},
}