To cite deepICMGP and its underlying deep GP methodology, use:

  Chang C, Sung C (2026). “Deep Intrinsic Coregionalization
  Multi-Output Gaussian Process Surrogate with Active Learning.”
  _International Journal for Uncertainty Quantification_, *16*(4),
  29-52. doi:10.1615/Int.J.UncertaintyQuantification.2026062570
  <https://doi.org/10.1615/Int.J.UncertaintyQuantification.2026062570>.

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning},
    author = {Chun-Yi Chang and Chih-Li Sung},
    journal = {International Journal for Uncertainty Quantification},
    year = {2026},
    volume = {16},
    number = {4},
    pages = {29--52},
    doi = {10.1615/Int.J.UncertaintyQuantification.2026062570},
  }

  Sauer A, Gramacy R, Higdon D (2023). “Active Learning for Deep
  Gaussian Process Surrogates.” _Technometrics_, *65*(1), 4-18.
  doi:10.1080/00401706.2021.2008505
  <https://doi.org/10.1080/00401706.2021.2008505>.

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Active Learning for Deep Gaussian Process Surrogates},
    author = {Annie Sauer and Robert B. Gramacy and David Higdon},
    journal = {Technometrics},
    year = {2023},
    volume = {65},
    number = {1},
    pages = {4--18},
    doi = {10.1080/00401706.2021.2008505},
  }

deepICMGP adapts code from the deepgp R package:
https://CRAN.R-project.org/package=deepgp. Use citation("deepgp") to
obtain the software citation for your installed version.