main.bbl

\begin{thebibliography}{xx}

\harvarditem{Abadi, Barham, Chen, Chen, Davis, Dean, Devin, Ghemawat, Irving,
  Isard et~al.}{2016}{abadi2016tensorflow}
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M.,
  Ghemawat, S., Irving, G., Isard, M. et~al.  \harvardyearleft
  2016\harvardyearright , {TensorFlow}: A system for large-scale machine
  learning., {\em in} `OSDI', Vol.~16, pp.~265--283.
\newline\harvardurl{\url{https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi}}

\harvarditem{Abadi, Chu, Goodfellow, McMahan, Mironov, Talwar \harvardand\
  Zhang}{2016}{abadi_deep_2016}
Abadi, M., Chu, A., Goodfellow, I., McMahan, H.~B., Mironov, I., Talwar, K.
  \harvardand\ Zhang, L.  \harvardyearleft 2016\harvardyearright , `Deep
  {Learning} with {Differential} {Privacy}', {\em Proceedings of the 2016 ACM
  SIGSAC Conference on Computer and Communications Security - CCS'16}
  pp.~308--318.
\newblock arXiv: 1607.00133.
\newline\harvardurl{\url{http://arxiv.org/abs/1607.00133}}

\harvarditem[Abadi et~al.]{Abadi, Isard \harvardand\ Murray}{2017}{tensorflow}
Abadi, M., Isard, M. \harvardand\ Murray, D.~G.  \harvardyearleft
  2017\harvardyearright , `A computational model for {TensorFlow}: an
  introduction', {\em Proceedings of the 1st ACM SIGPLAN International Workshop
  on Machine Learning and Programming Languages} pp.~1--7.
\newline\harvardurl{\url{http://doi.acm.org/10.1145/3088525.3088527}}

\harvarditem[Ackley et~al.]{Ackley, Hinton \harvardand\
  Sejnowski}{1985}{ackley_boltzmann_1985}
Ackley, D.~H., Hinton, G.~E. \harvardand\ Sejnowski, T.~J.  \harvardyearleft
  1985\harvardyearright , `A learning algorithm for {Boltzmann} machines', {\em
  Cognitive science} {\bf 9}(1),~147--169.
\newblock Publisher: Elsevier.
\newline\harvardurl{\url{https://doi.org/10.1016/S0364-0213(85)80012-4}}

\harvarditem[Aiello et~al.]{Aiello, Eckstrand, Fu, Landry \harvardand\
  Aboyoun}{2018}{h2o}
Aiello, S., Eckstrand, E., Fu, A., Landry, M. \harvardand\ Aboyoun, P.
  \harvardyearleft 2018\harvardyearright , `Machine {Learning} with
  \proglang{R} and {H2O}', {\em {H2O} booklet} {\bf 550}.
\newline\harvardurl{\url{https://www.h2o.ai/resources/}}

\harvarditem[Arnold et~al.]{Arnold, Gosling \harvardand\
  Holmes}{2005}{arnold2005java}
Arnold, K., Gosling, J. \harvardand\ Holmes, D.  \harvardyearleft
  2005\harvardyearright , {\em The Java programming language}, Addison Wesley
  Professional.

\harvarditem{Auguie}{2017}{gridExtra}
Auguie, B.  \harvardyearleft 2017\harvardyearright , {\em gridExtra:
  Miscellaneous Functions for "Grid" Graphics}.
\newblock R package version 2.3.
\newline\harvardurl{\url{https://CRAN.R-project.org/package=gridExtra}}

\harvarditem[Azur et~al.]{Azur, Stuart, Frangakis \harvardand\
  Leaf}{2011}{mice}
Azur, M.~J., Stuart, E.~A., Frangakis, C. \harvardand\ Leaf, P.~J.
  \harvardyearleft 2011\harvardyearright , `Multiple imputation by chained
  equations: what is it and how does it work?', {\em International Journal of
  Methods in Psychiatric Research} {\bf 20}(1),~40--49.
\newline\harvardurl{\url{https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/}}

\harvarditem[Bates et~al.]{Bates, Kornblith, Noack, Bouchet-Valat, Borregaard,
  Arslan, White, Kleinschmidt, Lynch, Dunning, Mogensen, Lendle, Aluthge,
  pdeffebach, Calderón, Born, Setzler, DuBois, Quinn, Bastide, Anthony~Blaom,
  König, Caine, Lin, Ngo, Adenbaum, TagBot \harvardand\ Hein}{2021}{juliaglm}
Bates, D., Kornblith, S., Noack, A., Bouchet-Valat, M., Borregaard, M.~K.,
  Arslan, A., White, J.~M., Kleinschmidt, D., Lynch, G., Dunning, I., Mogensen,
  P.~K., Lendle, S., Aluthge, D., pdeffebach, Calderón, J. B.~S., Born, B.,
  Setzler, B., DuBois, C., Quinn, J., Bastide, P., Anthony~Blaom, P., König,
  B., Caine, C., Lin, D., Ngo, H.~Q., Adenbaum, J., TagBot, J. \harvardand\
  Hein, L.  \harvardyearleft 2021\harvardyearright , `Julia package
  \apkg{GLM}'.
\newline\harvardurl{\url{https://zenodo.org/record/4556866}}

\harvarditem[Bates et~al.]{Bates, Lai, Byrne \harvardand\
  contributors}{2020}{rcallGithub}
Bates, D., Lai, R., Byrne, S. \harvardand\ contributors  \harvardyearleft
  2020\harvardyearright , `\proglang{Julia} package {RCall} ({GitHub}
  repository)'.
\newline\harvardurl{\url{https://github.com/JuliaInterop/RCall.jl}}

\harvarditem{Bengio}{2012}{bengio2012practical}
Bengio, Y.  \harvardyearleft 2012\harvardyearright , Practical recommendations
  for gradient-based training of deep architectures, {\em in} G.~Montavon,
  G.~B. Orr \harvardand\ K.-R. M{\"u}ller, eds, `Neural networks: Tricks of the
  trade', Springer, Berlin, Heidelberg, pp.~437--478.
\newline\harvardurl{\url{https://doi.org/10.1007/978-3-642-35289-8\_26}}

\harvarditem[Bergstra et~al.]{Bergstra, Bardenet, Bengio \harvardand\
  Kégl}{2011}{bergstra_algorithms_2011}
Bergstra, J., Bardenet, R., Bengio, Y. \harvardand\ Kégl, B.  \harvardyearleft
  2011\harvardyearright , Algorithms for {Hyper}-{Parameter} {Optimization},
  {\em in} J.~Shawe-Taylor, R.~Zemel, P.~Bartlett, F.~Pereira \harvardand\
  K.~Q. Weinberger, eds, `Advances in {Neural} {Information} {Processing}
  {Systems}', Vol.~24, Curran Associates, Inc., pp.~2546--2554.

\harvarditem[Besard et~al.]{Besard, Foket \harvardand\
  De~Sutter}{2018}{juliagpu}
Besard, T., Foket, C. \harvardand\ De~Sutter, B.  \harvardyearleft
  2018\harvardyearright , `Effective extensible programming: Unleashing {Julia}
  on {GPUs}', {\em IEEE Transactions on Parallel and Distributed Systems} .

\harvarditem[Bezanson et~al.]{Bezanson, Edelman, Karpinski \harvardand\
  Shah}{2017}{bezanson2017julia}
Bezanson, J., Edelman, A., Karpinski, S. \harvardand\ Shah, V.~B.
  \harvardyearleft 2017\harvardyearright , `Julia: A fresh approach to
  numerical computing', {\em SIAM Review} {\bf 59}(1),~65--98.
\newline\harvardurl{\url{http://doi.org/10.1137/141000671}}

\harvarditem{Bland \harvardand\ Altman}{2000}{blandaltmannodds}
Bland, J.~M. \harvardand\ Altman, D.~G.  \harvardyearleft 2000\harvardyearright
  , `The odds ratio', {\em BMJ} {\bf 320}(7247),~1468.
\newline\harvardurl{\url{https://www.bmj.com/content/320/7247/1468.1}}

\harvarditem[Blei et~al.]{Blei, Kucukelbir \harvardand\
  McAuliffe}{2017}{blei_variational_2017}
Blei, D.~M., Kucukelbir, A. \harvardand\ McAuliffe, J.~D.  \harvardyearleft
  2017\harvardyearright , `Variational inference: a review for statisticians',
  {\em Journal of the American statistical Association} {\bf
  112}(518),~859--877.
\newblock Publisher: Taylor \& Francis.

\harvarditem[Bonofiglio et~al.]{Bonofiglio, Schumacher \harvardand\
  Binder}{2020}{bonofiglio2020}
Bonofiglio, F., Schumacher, M. \harvardand\ Binder, H.  \harvardyearleft
  2020\harvardyearright , `Recovery of original individual person data ({IPD})
  inferences from empirical {IPD} summaries only: {Applications} to distributed
  computing under disclosure constraints', {\em Statistics in Medicine} {\bf
  39}(8),~1183--1198.
\newline\harvardurl{\url{https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.8470}}

\harvarditem[Bonomi et~al.]{Bonomi, Huang \harvardand\
  Ohno-Machado}{2020}{bonomi_privacy_2020}
Bonomi, L., Huang, Y. \harvardand\ Ohno-Machado, L.  \harvardyearleft
  2020\harvardyearright , `Privacy challenges and research opportunities for
  genomic data sharing', {\em Nature Genetics} {\bf 52}(7),~646--654.
\newline\harvardurl{\url{https://doi.org/10.1038/s41588-020-0651-0}}

\harvarditem[Bottou et~al.]{Bottou, Curtis \harvardand\
  Nocedal}{2018}{bottou_optimization_2018}
Bottou, L., Curtis, F.~E. \harvardand\ Nocedal, J.  \harvardyearleft
  2018\harvardyearright , `Optimization methods for large-scale machine
  learning', {\em Siam Review} {\bf 60}(2),~223--311.
\newblock Publisher: SIAM.
\newline\harvardurl{\url{https://doi.org/10.1137/16M1080173}}

\harvarditem{Bray}{2017}{jsonspec1}
Bray, T.  \harvardyearleft 2017\harvardyearright , {\em The {JavaScript}
  {Object} {Notation} ({JSON}) {Data} {Interchange} {Format}}.
\newblock Library Catalog: tools.ietf.org.
\newline\harvardurl{\url{https://tools.ietf.org/html/rfc8259}}

\harvarditem[Brooks et~al.]{Brooks, Gelman, Jones \harvardand\
  Meng}{2011}{mcmc_handbook_2011}
Brooks, S., Gelman, A., Jones, G. \harvardand\ Meng, X.-L.  \harvardyearleft
  2011\harvardyearright , {\em Handbook of Markov Chain Monte Carlo}, CRC
  Press.

\harvarditem[Brown et~al.]{Brown, Mann, Ryder, Subbiah, Kaplan, Dhariwal,
  Neelakantan, Shyam, Sastry, Askell, Agarwal, Herbert-Voss, Krueger, Henighan,
  Child, Ramesh, Ziegler, Wu, Winter, Hesse, Chen, Sigler, Litwin, Gray, Chess,
  Clark, Berner, McCandlish, Radford, Sutskever \harvardand\
  Amodei}{2020}{gpt3}
Brown, T.~B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P.,
  Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S.,
  Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler,
  D.~M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray,
  S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever,
  I. \harvardand\ Amodei, D.  \harvardyearleft 2020\harvardyearright ,
  `Language models are few-shot learners'.

\harvarditem[Budin-Ljøsne et~al.]{Budin-Ljøsne, Burton, Isaeva, Gaye, Turner,
  Murtagh, Wallace, Ferretti \harvardand\
  Harris}{2015}{budin-ljosne_datashield}
Budin-Ljøsne, I., Burton, P., Isaeva, J., Gaye, A., Turner, A., Murtagh,
  M.~J., Wallace, S., Ferretti, V. \harvardand\ Harris, J.~R.  \harvardyearleft
  2015\harvardyearright , `{DataSHIELD}: {An} {Ethically} {Robust} {Solution}
  to {Multiple}-{Site} {Individual}-{Level} {Data} {Analysis}', {\em Public
  Health Genomics} {\bf 18}(2),~87--96.
\newline\harvardurl{\url{https://www.karger.com/Article/FullText/368959}}

\harvarditem[Campos et~al.]{Campos, Zimek, Sander, Campello, Micenková,
  Schubert, Assent \harvardand\ Houle}{2016}{unsupervised_outlier}
Campos, G.~O., Zimek, A., Sander, J., Campello, R. J. G.~B., Micenková, B.,
  Schubert, E., Assent, I. \harvardand\ Houle, M.~E.  \harvardyearleft
  2016\harvardyearright , `On the evaluation of unsupervised outlier detection:
  measures, datasets, and an empirical study', {\em Data Mining and Knowledge
  Discovery} {\bf 30}(4),~891--927.
\newline\harvardurl{\url{https://doi.org/10.1007/s10618-015-0444-8}}

\harvarditem{Carreira-Perpinan \harvardand\
  Hinton}{2005}{perpinan_contrastive_2005}
Carreira-Perpinan, M.~A. \harvardand\ Hinton, G.~E.  \harvardyearleft
  2005\harvardyearright , On contrastive divergence learning, {\em in}
  `{AISTATS}', Vol.~10, Citeseer, pp.~33--40.

\harvarditem{Chambers}{2016}{chambersExtendingR}
Chambers, J.~M.  \harvardyearleft 2016\harvardyearright , {\em The {XR}
  Structure for Interfaces}, CRC Press, Boca Raton, Florida, chapter~13,
  pp.~259--301.

\harvarditem[Chan et~al.]{Chan, Sahiner, Wagner \harvardand\
  Petrick}{1999}{chan_classifier_1999}
Chan, H.-P., Sahiner, B., Wagner, R.~F. \harvardand\ Petrick, N.
  \harvardyearleft 1999\harvardyearright , `Classifier design for
  computer-aided diagnosis: {Effects} of finite sample size on the mean
  performance of classical and neural network classifiers', {\em Medical
  Physics} {\bf 26}(12),~2654--2668.

\harvarditem[Chang et~al.]{Chang, Balachandar, Lam, Yi, Brown, Beers, Rosen,
  Rubin \harvardand\ Kalpathy-Cramer}{2018}{chang_distributed}
Chang, K., Balachandar, N., Lam, C., Yi, D., Brown, J., Beers, A., Rosen, B.,
  Rubin, D.~L. \harvardand\ Kalpathy-Cramer, J.  \harvardyearleft
  2018\harvardyearright , `Distributed deep learning networks among
  institutions for medical imaging', {\em Journal of the American Medical
  Informatics Association} pp.~945--954.
\newline\harvardurl{\url{https://doi.org/10.1093/jamia/ocy017}}

\harvarditem[Chen et~al.]{Chen, Rubanova, Bettencourt \harvardand\
  Duvenaud}{2019}{chen_neural_2019}
Chen, R. T.~Q., Rubanova, Y., Bettencourt, J. \harvardand\ Duvenaud, D.
  \harvardyearleft 2019\harvardyearright , `Neural {Ordinary} {Differential}
  {Equations}', {\em arXiv:1806.07366 [cs, stat]} .
\newline\harvardurl{\url{http://arxiv.org/abs/1806.07366}}

\harvarditem[Chen et~al.]{Chen, Li, Li, Lin, Wang, Wang, Xiao, Xu, Zhang
  \harvardand\ Zhang}{2015}{mxnet}
Chen, T., Li, M., Li, Y., Lin, M., Wang, N., Wang, M., Xiao, T., Xu, B., Zhang,
  C. \harvardand\ Zhang, Z.  \harvardyearleft 2015\harvardyearright , `{MXNet}:
  {A} {Flexible} and {Efficient} {Machine} {Learning} {Library} for
  {Heterogeneous} {Distributed} {Systems}', {\em arXiv:1512.01274 [cs]} .
\newline\harvardurl{\url{http://arxiv.org/abs/1512.01274}}

\harvarditem[Cho et~al.]{Cho, Ilin \harvardand\ Raiko}{2011}{cho2011improved}
Cho, K., Ilin, A. \harvardand\ Raiko, T.  \harvardyearleft
  2011\harvardyearright , `Improved learning of {Gaussian-Bernoulli} restricted
  {Boltzmann} machines', {\em Artificial Neural Networks and Machine
  Learning--ICANN 2011} pp.~10--17.
\newline\harvardurl{\url{https://doi.org/10.1007/978-3-642-21735-7_2}}

\harvarditem[Choi et~al.]{Choi, Biswal, Malin, Duke, Stewart \harvardand\
  Sun}{2017}{choi_generating_2017}
Choi, E., Biswal, S., Malin, B., Duke, J., Stewart, W.~F. \harvardand\ Sun, J.
  \harvardyearleft 2017\harvardyearright , Generating {Multi}-label {Discrete}
  {Patient} {Records} using {Generative} {Adversarial} {Networks}, {\em in}
  `Proceedings of {Machine} {Learning} for {Healthcare} 2017', Northeastern
  University, Boston, Massachusetts, p.~21.
\newline\harvardurl{\url{http://proceedings.mlr.press/v68/choi17a.html}}

\harvarditem{Cohn}{2018}{cohn_ai_2018}
Cohn, G.  \harvardyearleft 2018\harvardyearright , `{AI} {Art} at
  {Christie}’s {Sells} for \$432,500', {\em The New York Times} .
\newline\harvardurl{\url{https://www.nytimes.com/2018/10/25/arts/design/ai-art-sold-christies.html}}

\harvarditem{Curry}{1944}{gradientdescent}
Curry, H.~B.  \harvardyearleft 1944\harvardyearright , `The method of steepest
  descent for non-linear minimization problems', {\em Quarterly of Applied
  Mathematics} {\bf 2}(3),~258--261.
\newline\harvardurl{\url{https://doi.org/10.1090/qam/10667}}

\harvarditem{Diestel}{2016}{diestelgraph}
Diestel, R.  \harvardyearleft 2016\harvardyearright , {\em Graph Theory}, 5
  edn, Springer-Verlag, Heidelberg, Germany.

\harvarditem[Ding et~al.]{Ding, Condon \harvardand\
  Shah}{2018}{ding_interpretable_2018}
Ding, J., Condon, A. \harvardand\ Shah, S.~P.  \harvardyearleft
  2018\harvardyearright , `Interpretable dimensionality reduction of single
  cell transcriptome data with deep generative models', {\em Nature
  Communications} {\bf 9}(1),~2002.
\newline\harvardurl{\url{https://www.nature.com/articles/s41467-018-04368-5}}

\harvarditem{Dinur \harvardand\ Nissim}{2003}{dinur_revealing_2003}
Dinur, I. \harvardand\ Nissim, K.  \harvardyearleft 2003\harvardyearright ,
  Revealing information while preserving privacy, {\em in} `Proceedings of the
  twenty-second {ACM} {SIGMOD}-{SIGACT}-{SIGART} symposium on {Principles} of
  database systems', {PODS} '03, Association for Computing Machinery, New York,
  NY, USA, pp.~202--210.
\newline\harvardurl{\url{https://doi.org/10.1145/773153.773173}}

\harvarditem[Doiron et~al.]{Doiron, Burton, Marcon, Gaye, Wolffenbuttel,
  Perola, Stolk, Foco, Minelli, Waldenberger, Holle, Kvaløy, Hillege, Tassé,
  Ferretti \harvardand\ Fortier}{2013}{doiron_datashield_2013}
Doiron, D., Burton, P., Marcon, Y., Gaye, A., Wolffenbuttel, B. H.~R., Perola,
  M., Stolk, R.~P., Foco, L., Minelli, C., Waldenberger, M., Holle, R.,
  Kvaløy, K., Hillege, H.~L., Tassé, A.-M., Ferretti, V. \harvardand\
  Fortier, I.  \harvardyearleft 2013\harvardyearright , `Data harmonization and
  federated analysis of population-based studies: the {BioSHaRE} project', {\em
  Emerging Themes in Epidemiology} {\bf 10}(1),~12.
\newline\harvardurl{\url{https://doi.org/10.1186/1742-7622-10-12}}

\harvarditem[Doiron et~al.]{Doiron, Marcon, Fortier, Burton \harvardand\
  Ferretti}{2017}{opal}
Doiron, D., Marcon, Y., Fortier, I., Burton, P. \harvardand\ Ferretti, V.
  \harvardyearleft 2017\harvardyearright , `Software {Application} {Profile}:
  {Opal} and {Mica}: open-source software solutions for epidemiological data
  management, harmonization and dissemination', {\em International Journal of
  Epidemiology} {\bf 46}(5),~1372--1378.
\newline\harvardurl{\url{https://doi.org/10.1093/ije/dyx180}}

\harvarditem{Dowle \harvardand\ Srinivasan}{2020}{datatable}
Dowle, M. \harvardand\ Srinivasan, A.  \harvardyearleft 2020\harvardyearright ,
  {\em data.table: Extension of \inlinecode{data.frame}}.
\newblock R package version 1.13.4.
\newline\harvardurl{\url{https://CRAN.R-project.org/package=data.table}}

\harvarditem{Drees}{2009}{darch}
Drees, M.  \harvardyearleft 2009\harvardyearright , {Implementierung} und
  {Analyse} von tiefen {Architekturen} in {R}, Master's thesis, Fachhochschule
  Dortmund, Germany.

\harvarditem{Dwork}{2008}{dwork_differential_2008}
Dwork, C.  \harvardyearleft 2008\harvardyearright , Differential {Privacy}: {A}
  {Survey} of {Results}, {\em in} M.~Agrawal, D.~Du, Z.~Duan \harvardand\
  A.~Li, eds, `Theory and {Applications} of {Models} of {Computation}', Lecture
  {Notes} in {Computer} {Science}, Springer, Berlin, Heidelberg, pp.~1--19.
\newline\harvardurl{\url{https://doi.org/10.1007/978-3-540-79228-4_1}}

\harvarditem[Eisen et~al.]{Eisen, Spellman, Brown \harvardand\
  Botstein}{1998}{eisen_cluster_1998}
Eisen, M.~B., Spellman, P.~T., Brown, P.~O. \harvardand\ Botstein, D.
  \harvardyearleft 1998\harvardyearright , `Cluster analysis and display of
  genome-wide expression patterns', {\em Proceedings of the National Academy of
  Sciences} {\bf 95}(25),~14863--14868.
\newblock Publisher: National Academy of Sciences, Section: Biological
  Sciences.
\newline\harvardurl{\url{https://www.pnas.org/content/95/25/14863}}

\harvarditem{Faraway}{2002}{faraway_regression}
Faraway, J.~J.  \harvardyearleft 2002\harvardyearright , {\em Practical
  regression and {ANOVA} using {R}}, University of Michigan.
\newblock Available from
  \url{https://cran.r-project.org/doc/contrib/Faraway-PRA.pdf}.

\harvarditem[Gaye et~al.]{Gaye, Marcon, Isaeva, LaFlamme, Turner, Jones,
  Minion, Boyd, Newby, Nuotio, Wilson, Butters, Murtagh, Demir, Doiron,
  Giepmans, Wallace, Budin-Ljøsne, Schmidt, Boffetta, Boniol, Bota, Carter,
  deKlerk, Dibben, Francis, Hiekkalinna, Hveem, Kvaløy, Millar, Perry, Peters,
  Phillips, Popham, Raab, Reischl, Sheehan, Waldenberger, Perola, Heuvel,
  Macleod, Knoppers, Stolk, Fortier, Harris, Woffenbuttel, Murtagh, Ferretti
  \harvardand\ Burton}{2014}{gaye_datashield}
Gaye, A., Marcon, Y., Isaeva, J., LaFlamme, P., Turner, A., Jones, E.~M.,
  Minion, J., Boyd, A.~W., Newby, C.~J., Nuotio, M.-L., Wilson, R., Butters,
  O., Murtagh, B., Demir, I., Doiron, D., Giepmans, L., Wallace, S.~E.,
  Budin-Ljøsne, I., Schmidt, C.~O., Boffetta, P., Boniol, M., Bota, M.,
  Carter, K.~W., deKlerk, N., Dibben, C., Francis, R.~W., Hiekkalinna, T.,
  Hveem, K., Kvaløy, K., Millar, S., Perry, I.~J., Peters, A., Phillips,
  C.~M., Popham, F., Raab, G., Reischl, E., Sheehan, N., Waldenberger, M.,
  Perola, M., Heuvel, E. v.~d., Macleod, J., Knoppers, B.~M., Stolk, R.~P.,
  Fortier, I., Harris, J.~R., Woffenbuttel, B.~H., Murtagh, M.~J., Ferretti, V.
  \harvardand\ Burton, P.~R.  \harvardyearleft 2014\harvardyearright ,
  `{DataSHIELD}: taking the analysis to the data, not the data to the
  analysis', {\em International Journal of Epidemiology} {\bf
  43}(6),~1929--1944.
\newline\harvardurl{\url{http://ije.oxfordjournals.org/content/43/6/1929}}

\harvarditem{Geman \harvardand\ Geman}{1984}{gibbssamplingorig}
Geman, S. \harvardand\ Geman, D.  \harvardyearleft 1984\harvardyearright ,
  `Stochastic relaxation, {Gibbs} distributions, and the {Bayesian} restoration
  of images', {\em IEEE Transactions on Pattern Analysis and Machine
  Intelligence} {\bf PAMI-6}(6),~721--741.
\newblock Conference Name: IEEE Transactions on Pattern Analysis and Machine
  Intelligence.
\newline\harvardurl{\url{https://doi.org/10.1109/TPAMI.1984.4767596}}

\harvarditem{{\em GNU General Public License}}{2007}{gplv3}
{\em GNU General Public License}  \harvardyearleft 2007\harvardyearright .
\newline\harvardurl{\url{http://www.gnu.org/licenses/gpl.html}}

\harvarditem[Goncalves et~al.]{Goncalves, Ray, Soper, Stevens, Coyle
  \harvardand\ Sales}{2020}{goncalves}
Goncalves, A., Ray, P., Soper, B., Stevens, J., Coyle, L. \harvardand\ Sales,
  A.~P.  \harvardyearleft 2020\harvardyearright , `Generation and evaluation of
  synthetic patient data', {\em BMC Medical Research Methodology} {\bf
  20},~1--40.
\newblock Publisher: Springer.
\newline\harvardurl{\url{https://doi.org/10.1186/s12874-020-00977-1}}

\harvarditem[Goodfellow et~al.]{Goodfellow, Bengio \harvardand\
  Courville}{2016}{goodfellow_deep_2016}
Goodfellow, I., Bengio, Y. \harvardand\ Courville, A.  \harvardyearleft
  2016\harvardyearright , {\em Deep {Learning}}, MIT Press.
\newline\harvardurl{\url{http://www.deeplearningbook.org}}

\harvarditem[Goodfellow et~al.]{Goodfellow, Pouget-Abadie, Mirza, Xu,
  Warde-Farley, Ozair, Courville \harvardand\
  Bengio}{2014}{goodfellow_generative_2014}
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair,
  S., Courville, A. \harvardand\ Bengio, Y.  \harvardyearleft
  2014\harvardyearright , Generative {Adversarial} {Nets}, {\em in}
  Z.~Ghahramani, M.~Welling, C.~Cortes, N.~D. Lawrence \harvardand\ K.~Q.
  Weinberger, eds, `Advances in {Neural} {Information} {Processing} {Systems}
  27', Curran Associates, Inc., pp.~2672--2680.
\newline\harvardurl{\url{https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf}}

\harvarditem[Gruendner et~al.]{Gruendner, Prokosch, Schindler, Lenz
  \harvardand\ Binder}{2019}{gruendner}
Gruendner, J., Prokosch, H.-U., Schindler, S., Lenz, S. \harvardand\ Binder, H.
   \harvardyearleft 2019\harvardyearright , `A {Queue}-{Poll} {Extension} and
  {DataSHIELD}: {Standardised}, {Monitored}, {Indirect} and {Secure} {Access}
  to {Sensitive} {Data}.', {\em Studies in health technology and informatics}
  {\bf 258},~115--119.

\harvarditem[Harris et~al.]{Harris, Millman, van~der Walt, Gommers, Virtanen,
  Cournapeau, Wieser, Taylor, Berg, Smith, Kern, Picus, Hoyer, van Kerkwijk,
  Brett, Haldane, del R{'{\i}}o, Wiebe, Peterson, G{'{e}}rard-Marchant,
  Sheppard, Reddy, Weckesser, Abbasi, Gohlke \harvardand\
  Oliphant}{2020}{numpy}
Harris, C.~R., Millman, K.~J., van~der Walt, S.~J., Gommers, R., Virtanen, P.,
  Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N.~J., Kern, R.,
  Picus, M., Hoyer, S., van Kerkwijk, M.~H., Brett, M., Haldane, A., del
  R{'{\i}}o, J.~F., Wiebe, M., Peterson, P., G{'{e}}rard-Marchant, P.,
  Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C. \harvardand\
  Oliphant, T.~E.  \harvardyearleft 2020\harvardyearright , `Array programming
  with {NumPy}', {\em Nature} {\bf 585}(7825),~357--362.
\newline\harvardurl{\url{https://doi.org/10.1038/s41586-020-2649-2}}

\harvarditem[Hastie et~al.]{Hastie, Tibshirani \harvardand\
  Friedman}{2009}{hastie_elements}
Hastie, T., Tibshirani, R. \harvardand\ Friedman, J.  \harvardyearleft
  2009\harvardyearright , {\em The elements of statistical learning: data
  mining, inference, and prediction}, Springer series in statistics, 2 edn,
  Springer.

\harvarditem[Hayes et~al.]{Hayes, Melis, Danezis \harvardand\
  Cristofaro}{2019}{hayes_logan_2019}
Hayes, J., Melis, L., Danezis, G. \harvardand\ Cristofaro, E.~D.
  \harvardyearleft 2019\harvardyearright , `{LOGAN}: {Membership} {Inference}
  {Attacks} {Against} {Generative} {Models}', {\em Proceedings on Privacy
  Enhancing Technologies} {\bf 2019}(1),~133--152.
\newline\harvardurl{\url{https://doi.org/10.2478/popets-2019-0008}}

\harvarditem[He et~al.]{He, Zhang, Ren \harvardand\ Sun}{2015}{resnet}
He, K., Zhang, X., Ren, S. \harvardand\ Sun, J.  \harvardyearleft
  2015\harvardyearright , `Deep residual learning for image recognition', {\em
  arXiv preprint arXiv:1512.03385} .

\harvarditem[Hess et~al.]{Hess, Hackenberg \harvardand\
  Binder}{2020}{hess_exploring_2020}
Hess, M., Hackenberg, M. \harvardand\ Binder, H.  \harvardyearleft
  2020\harvardyearright , `Exploring generative deep learning for omics data
  using log-linear models', {\em Bioinformatics} {\bf 36}(20),~5045--5053.
\newline\harvardurl{\url{https://doi.org/10.1093/bioinformatics/btaa623}}

\harvarditem[Hess et~al.]{Hess, Lenz, Bl{\"a}tte, Bullinger \harvardand\
  Binder}{2017}{hess2017partitioned}
Hess, M., Lenz, S., Bl{\"a}tte, T.~J., Bullinger, L. \harvardand\ Binder, H.
  \harvardyearleft 2017\harvardyearright , `Partitioned learning of deep
  {Boltzmann} machines for {SNP} data', {\em Bioinformatics} {\bf
  33}(20),~3173--3180.
\newline\harvardurl{\url{https://doi.org/10.1093/bioinformatics/btx408}}

\harvarditem{Hinton}{2002}{cdorig}
Hinton, G.~E.  \harvardyearleft 2002\harvardyearright , `Training products of
  experts by minimizing {Contrastive} {Divergence}', {\em Neural Computation}
  {\bf 14}(8),~1771--1800.
\newblock Publisher: MIT Press.
\newline\harvardurl{\url{https://doi.org/10.1162/089976602760128018}}

\harvarditem{Hinton}{2012}{hinton_practical_2012}
Hinton, G.~E.  \harvardyearleft 2012\harvardyearright , A practical guide to
  training restricted {Boltzmann} machines, {\em in} G.~Montavon, G.~B. Orr
  \harvardand\ K.-R. Müller, eds, `Neural {Networks}: {Tricks} of the {Trade}:
  {Second} {Edition}', Springer Nature, pp.~599--619.
\newline\harvardurl{\url{https://doi.org/10.1007/978-3-642-35289-8_32}}

\harvarditem{Hinton \harvardand\ Salakhutdinov}{2006}{hinton_reducing_2006}
Hinton, G.~E. \harvardand\ Salakhutdinov, R.~R.  \harvardyearleft
  2006\harvardyearright , `Reducing the dimensionality of data with neural
  networks', {\em Science} {\bf 313}(5786),~504--507.
\newline\harvardurl{\url{http://science.sciencemag.org/content/313/5786/504}}

\harvarditem{Hinton \harvardand\ Sejnowski}{1999}{sejnowski_unsupervised_1999}
Hinton, G. \harvardand\ Sejnowski, T.~J.  \harvardyearleft
  1999\harvardyearright , {\em Unsupervised {Learning}: {Foundations} of
  {Neural} {Computation}}, MIT Press.

\harvarditem{Howie \harvardand\ Marchini}{2015}{impute_1000_genomes}
Howie, B. \harvardand\ Marchini, J.  \harvardyearleft 2015\harvardyearright ,
  `1,000 {Genomes} haplotypes - {Phase} 3 integrated variant set release in
  {NCBI} build 37 (hg19) coordinates'.
\newline\harvardurl{\url{https://mathgen.stats.ox.ac.uk/impute/1000GP\_Phase3.html}}

\harvarditem[Howie et~al.]{Howie, Donnelly \harvardand\
  Marchini}{2009}{impute2}
Howie, B.~N., Donnelly, P. \harvardand\ Marchini, J.  \harvardyearleft
  2009\harvardyearright , `A flexible and accurate genotype imputation method
  for the next generation of genome-wide association studies', {\em PLoS Genet}
  {\bf 5}(6),~e1000529.
\newblock Publisher: Public Library of Science.

\harvarditem[Huber et~al.]{Huber, Carey, Gentleman, Anders, Carlson, Carvalho,
  Bravo, Davis, Gatto, Girke, Gottardo, Hahne, Hansen, Irizarry, Lawrence,
  Love, MacDonald, Obenchain, {Ole's}, {Pag`es}, Reyes, Shannon, Smyth,
  Tenenbaum, Waldron \harvardand\ Morgan}{2015}{bioconductor}
Huber, W., Carey, V.~J., Gentleman, R., Anders, S., Carlson, M., Carvalho,
  B.~S., Bravo, H.~C., Davis, S., Gatto, L., Girke, T., Gottardo, R., Hahne,
  F., Hansen, K.~D., Irizarry, R.~A., Lawrence, M., Love, M.~I., MacDonald, J.,
  Obenchain, V., {Ole's}, A.~K., {Pag`es}, H., Reyes, A., Shannon, P., Smyth,
  G.~K., Tenenbaum, D., Waldron, L. \harvardand\ Morgan, M.  \harvardyearleft
  2015\harvardyearright , `{O}rchestrating high-throughput genomic analysis
  with {B}ioconductor', {\em Nature Methods} {\bf 12}(2),~115--121.
\newline\harvardurl{\url{https://doi.org/10.1038/nmeth.3252}}

\harvarditem{IEEE}{1985}{floatingpointstandard}
IEEE  \harvardyearleft 1985\harvardyearright , `{IEEE} standard for binary
  floating-point arithmetic', {\em ANSI/IEEE Std 754-1985} pp.~1--20.
\newline\harvardurl{\url{https://doi.org/10.1109/IEEESTD.1985.82928}}

\harvarditem{Innes}{2018}{flux}
Innes, M.  \harvardyearleft 2018\harvardyearright , `Flux: {Elegant} machine
  learning with \proglang{Julia}.', {\em Journal of Open Source Software} {\bf
  3}(25),~602.
\newline\harvardurl{\url{https://doi.org/10.21105/joss.00602}}

\harvarditem{{ISO/IEC}}{1998}{cppstandard}
{ISO/IEC}  \harvardyearleft 1998\harvardyearright , {\em {ISO International
  Standard ISO/IEC 14882:1998}: {Programming} language --- {C++}},
  International Organization for Standardization (ISO), Geneva, Switzerland.

\harvarditem[Jones et~al.]{Jones, Arthur, Nagy, Gowda, Godisemo, Holy,
  Mattriks, Noack, Sengupta, Darakananda, Leblanc, Dunning, Fischer, Chudzicki,
  Piibeleht, Yu, Breloff, Kleinschmidt, Mellnik, Verzani, inkyu, Innes,
  Huchette, Bauman, Hyatt, Forsyth, Borje, Saba, Coalson \harvardand\
  Pelenitsyn}{2018}{gadfly}
Jones, D.~C., Arthur, B., Nagy, T., Gowda, S., Godisemo, Holy, T., Mattriks,
  Noack, A., Sengupta, A., Darakananda, D., Leblanc, S., Dunning, I., Fischer,
  K., Chudzicki, D., Piibeleht, M., Yu, Y., Breloff, T., Kleinschmidt, D.,
  Mellnik, A., Verzani, J., inkyu, Innes, M.~J., Huchette, J., Bauman, M.,
  Hyatt, K., Forsyth, J., Borje, G., Saba, E., Coalson, C. \harvardand\
  Pelenitsyn, A.  \harvardyearleft 2018\harvardyearright ,
  `{GiovineItalia}/{Gadfly.jl}: Crafty statistical graphics for {Julia}'.
\newline\harvardurl{\url{https://doi.org/10.5281/zenodo.1924781}}

\harvarditem{{Julia Computing, Inc.}}{2020}{juliadbGithub}
{Julia Computing, Inc.}  \harvardyearleft 2020\harvardyearright ,
  `\proglang{Julia} package {JuliaDB} ({GitHub} repository)'.
\newblock Version 0.13.0.
\newline\harvardurl{\url{https://github.com/JuliaComputing/JuliaDB.jl}}

\harvarditem{{Julia Data collaborators}}{2020}{juliaDataFramesGithub}
{Julia Data collaborators}  \harvardyearleft 2020\harvardyearright ,
  `\proglang{Julia} package {DataFrames} ({GitHub} repository)'.
\newblock original-date: 2012-07-11T18:00:09Z.
\newline\harvardurl{\url{https://github.com/JuliaData/DataFrames.jl}}

\harvarditem{Kifer \harvardand\ Machanavajjhala}{2011}{kifer_no_2011}
Kifer, D. \harvardand\ Machanavajjhala, A.  \harvardyearleft
  2011\harvardyearright , No free lunch in data privacy, {\em in} `Proceedings
  of the 2011 {ACM} {SIGMOD} {International} {Conference} on {Management} of
  data', {SIGMOD} '11, Association for Computing Machinery, New York, NY, USA,
  pp.~193--204.
\newline\harvardurl{\url{https://doi.org/10.1145/1989323.1989345}}

\harvarditem{Kingma \harvardand\ Welling}{2014}{Kingma2013}
Kingma, D.~P. \harvardand\ Welling, M.  \harvardyearleft 2014\harvardyearright
  , Auto-encoding variational bayes, {\em in} Y.~Bengio \harvardand\ Y.~LeCun,
  eds, `2nd International Conference on Learning Representations ({ICLR}),
  Conference Track Proceedings'.
\newline\harvardurl{\url{https://arxiv.org/abs/1312.6114}}

\harvarditem{Krizhevsky}{2009}{krizhevsky2009tinyimagesthesis}
Krizhevsky, A.  \harvardyearleft 2009\harvardyearright , Learning multiple
  layers of features from tiny images, Master's thesis, University of Toronto,
  Canada.
\newline\harvardurl{\url{https://www.cs.utoronto.ca/~kriz/learning-features-2009-TR.pdf}}

\harvarditem{LeCun}{2019{\em a}}{lecun_dlhardware}
LeCun, Y.  \harvardyearleft 2019{\em a}\harvardyearright , 1.1 {Deep}
  {Learning} {Hardware}: {Past}, {Present}, and {Future}, {\em in} `2019 {IEEE}
  {International} {Solid}-{State} {Circuits} {Conference} - ({ISSCC})',
  pp.~12--19.
\newblock ISSN: 2376-8606.
\newline\harvardurl{\url{http://doi.org/10.1109/ISSCC.2019.8662396}}

\harvarditem{LeCun}{2019{\em b}}{lecun_selfsupervised_2019}
LeCun, Y.  \harvardyearleft 2019{\em b}\harvardyearright , `Facebook post about
  self-supervised learning'.
\newline\harvardurl{\url{https://www.facebook.com/722677142/posts/10155934004262143/}}

\harvarditem[LeCun et~al.]{LeCun, Bengio \harvardand\
  Hinton}{2015}{lecun_deep_learning_2015}
LeCun, Y., Bengio, Y. \harvardand\ Hinton, G.  \harvardyearleft
  2015\harvardyearright , `Deep learning', {\em Nature} {\bf
  521}(7553),~436--444.
\newblock Number: 7553 Publisher: Nature Publishing Group.
\newline\harvardurl{\url{https://www.nature.com/articles/nature14539}}

\harvarditem{Lenz, Hackenberg \harvardand\ Binder}{2021}{juliaconnector_2021}
Lenz, S., Hackenberg, M. \harvardand\ Binder, H.  \harvardyearleft
  2021\harvardyearright , `The {JuliaConnectoR}: a functionally oriented
  interface for integrating {Julia} in {R}', {\em arXiv:2005.06334 [cs, stat]}
  .
\newline\harvardurl{\url{http://arxiv.org/abs/2005.06334}}

\harvarditem{Lenz, Hess \harvardand\ Binder}{2021}{dsdbm}
Lenz, S., Hess, M. \harvardand\ Binder, H.  \harvardyearleft
  2021\harvardyearright , `Deep generative models in {DataSHIELD}', {\em BMC
  Medical Research Methodology} {\bf 21}(1),~64.
\newline\harvardurl{\url{https://doi.org/10.1186/s12874-021-01237-6}}

\harvarditem{Li}{2019}{JuliaCallPaper}
Li, C.  \harvardyearleft 2019\harvardyearright , `{JuliaCall}: an \proglang{R}
  package for seamless integration between \proglang{R} and \proglang{Julia}',
  {\em Journal of Open Source Software} {\bf 4}(35),~1284.
\newline\harvardurl{\url{https://doi.org/10.21105/joss.01284}}

\harvarditem[Li et~al.]{Li, Li \harvardand\
  Venkatasubramanian}{2007}{li_t-closeness:_2007}
Li, N., Li, T. \harvardand\ Venkatasubramanian, S.  \harvardyearleft
  2007\harvardyearright , t-{Closeness}: {Privacy} {Beyond} k-{Anonymity} and
  l-{Diversity}, {\em in} `2007 {IEEE} 23rd {International} {Conference} on
  {Data} {Engineering}', pp.~106--115.

\harvarditem[Li et~al.]{Li, Qardaji, Su, Wu \harvardand\
  Yang}{2013}{li_membership_2013}
Li, N., Qardaji, W., Su, D., Wu, Y. \harvardand\ Yang, W.  \harvardyearleft
  2013\harvardyearright , Membership privacy: a unifying framework for privacy
  definitions, {\em in} `Proceedings of the 2013 {ACM} {SIGSAC} conference on
  {Computer} \& communications security', {CCS} '13, Association for Computing
  Machinery, New York, NY, USA, pp.~889--900.
\newline\harvardurl{\url{https://doi.org/10.1145/2508859.2516686}}

\harvarditem[Luraschi et~al.]{Luraschi, Kuo, Ushey, Allaire, Macedo, Falaki,
  Wang, Zhang, Li, Hajnala, Szymkiewicz, Davis, {RStudio, Inc.} \harvardand\
  {The Apache Software Foundation}}{2020}{sparklyr}
Luraschi, J., Kuo, K., Ushey, K., Allaire, J., Macedo, S., Falaki, H., Wang,
  L., Zhang, A., Li, Y., Hajnala, J., Szymkiewicz, M., Davis, W., {RStudio,
  Inc.} \harvardand\ {The Apache Software Foundation}  \harvardyearleft
  2020\harvardyearright , {\em \apkg{sparklyr}: \proglang{R} {Interface} for
  {Apache} {Spark}}.
\newblock \proglang{R}~package version~1.5.2.
\newline\harvardurl{\url{https://CRAN.R-project.org/package=sparklyr}}

\harvarditem[Machanavajjhala et~al.]{Machanavajjhala, Kifer, Gehrke
  \harvardand\ Venkitasubramaniam}{2007}{machanavajjhala_l-diversity_2007}
Machanavajjhala, A., Kifer, D., Gehrke, J. \harvardand\ Venkitasubramaniam, M.
  \harvardyearleft 2007\harvardyearright , `\textit{{L}}-diversity: {Privacy}
  beyond \textit{k}-anonymity', {\em ACM Transactions on Knowledge Discovery
  from Data} {\bf 1}(1),~3--es.
\newline\harvardurl{\url{https://doi.org/10.1145/1217299.1217302}}

\harvarditem{Malmaud \harvardand\ White}{2018}{tensorflowjl}
Malmaud, J. \harvardand\ White, L.  \harvardyearleft 2018\harvardyearright ,
  `{TensorFlow}.jl: {An} {Idiomatic} {Julia} {Front} {End} for {TensorFlow}',
  {\em Journal of Open Source Software} {\bf 3}(31),~1002.
\newline\harvardurl{\url{https://joss.theoj.org/papers/10.21105/joss.01002}}

\harvarditem{Manrique‐Vallier \harvardand\
  Hu}{2018}{manriquevallier_bayesian_2018}
Manrique‐Vallier, D. \harvardand\ Hu, J.  \harvardyearleft
  2018\harvardyearright , `Bayesian non-parametric generation of fully
  synthetic multivariate categorical data in the presence of structural zeros',
  {\em Journal of the Royal Statistical Society: Series A (Statistics in
  Society)} {\bf 181}(3),~635--647.
\newline\harvardurl{\url{https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/rssa.12352}}

\harvarditem[Martens et~al.]{Martens, Chattopadhya, Pitassi \harvardand\
  Zemel}{2013}{martens_representational_2013}
Martens, J., Chattopadhya, A., Pitassi, T. \harvardand\ Zemel, R.
  \harvardyearleft 2013\harvardyearright , On the {Representational}
  {Efficiency} of {Restricted} {Boltzmann} {Machines}, {\em in} C.~J.~C.
  Burges, L.~Bottou, M.~Welling, Z.~Ghahramani \harvardand\ K.~Q. Weinberger,
  eds, `Advances in {Neural} {Information} {Processing} {Systems}', Vol.~26,
  Curran Associates, Inc.
\newline\harvardurl{\url{https://proceedings.neurips.cc/paper/2013/file/7bb060764a818184ebb1cc0d43d382aa-Paper.pdf}}

\harvarditem{{Massachusetts Institute of Technology}}{1988}{mitlicense}
{Massachusetts Institute of Technology}  \harvardyearleft 1988\harvardyearright
  , `{MIT} license'.
\newline\harvardurl{\url{https://opensource.org/licenses/MIT}}

\harvarditem{Masters \harvardand\ Luschi}{2018}{masters_revisiting_2018}
Masters, D. \harvardand\ Luschi, C.  \harvardyearleft 2018\harvardyearright ,
  `Revisiting {Small} {Batch} {Training} for {Deep} {Neural} {Networks}', {\em
  arXiv:1804.07612 [cs, stat]} .
\newline\harvardurl{\url{http://arxiv.org/abs/1804.07612}}

\harvarditem{McCoy \harvardand\ Wu}{2014}{isingmodel}
McCoy, B.~M. \harvardand\ Wu, T.~T.  \harvardyearleft 2014\harvardyearright ,
  {\em The Two-Dimensional {Ising} Model}, 2 edn, Courier Corporation.

\harvarditem{McCulloch \harvardand\ Pitts}{1943}{mcculloch_logical_1943}
McCulloch, W.~S. \harvardand\ Pitts, W.  \harvardyearleft 1943\harvardyearright
  , `A logical calculus of the ideas immanent in nervous activity', {\em The
  bulletin of mathematical biophysics} {\bf 5}(4),~115--133.
\newline\harvardurl{\url{https://doi.org/10.1007/BF02478259}}

\harvarditem{{M}c{K}inney}{2010}{pandas}
{M}c{K}inney, W.  \harvardyearleft 2010\harvardyearright , {D}ata {S}tructures
  for {S}tatistical {C}omputing in {P}ython, {\em in} {S}t\'efan van~der {W}alt
  \harvardand\ {J}arrod {M}illman, eds, `{P}roceedings of the 9th {P}ython in
  {S}cience {C}onference', pp.~56 -- 61.
\newline\harvardurl{\url{http://doi.org/10.25080/Majora-92bf1922-00a}}

\harvarditem[Midha et~al.]{Midha, Singh, Palvia \harvardand\
  Kshetri}{2010}{midha_improving_2010}
Midha, V., Singh, R., Palvia, P. \harvardand\ Kshetri, N.  \harvardyearleft
  2010\harvardyearright , `Improving {Open} {Source} {Software} {Maintenance}',
  {\em Journal of Computer Information Systems} {\bf 50}(3),~81--90.
\newblock Publisher: Taylor \& Francis.
\newline\harvardurl{\url{https://www.tandfonline.com/doi/abs/10.1080/08874417.2010.11645410}}

\harvarditem[Min et~al.]{Min, Lee \harvardand\ Yoon}{2017}{min_deep_2017}
Min, S., Lee, B. \harvardand\ Yoon, S.  \harvardyearleft 2017\harvardyearright
  , `Deep learning in bioinformatics', {\em Briefings in Bioinformatics} {\bf
  18}(5),~851--869.
\newline\harvardurl{\url{https://doi.org/10.1093/bib/bbw068}}

\harvarditem{Mirza \harvardand\ Osindero}{2014}{cgan}
Mirza, M. \harvardand\ Osindero, S.  \harvardyearleft 2014\harvardyearright ,
  `Conditional {Generative} {Adversarial} {Nets}', {\em arXiv:1411.1784 [cs,
  stat]} .
\newblock arXiv: 1411.1784.
\newline\harvardurl{\url{http://arxiv.org/abs/1411.1784}}

\harvarditem{Müller \harvardand\ Wickham}{2020}{tibble}
Müller, K. \harvardand\ Wickham, H.  \harvardyearleft 2020\harvardyearright ,
  {\em tibble: Simple Data Frames}.
\newblock R package version 3.0.4.
\newline\harvardurl{\url{https://CRAN.R-project.org/package=tibble}}

\harvarditem{{MongoDB, Inc.}}{2009}{bsonspec}
{MongoDB, Inc.}  \harvardyearleft 2009\harvardyearright , `{BSON} ({Binary}
  {JSON}) serialization'.
\newline\harvardurl{\url{http://bsonspec.org/}}

\harvarditem{Murtagh \harvardand\ Contreras}{2012}{hclust}
Murtagh, F. \harvardand\ Contreras, P.  \harvardyearleft 2012\harvardyearright
  , `Algorithms for hierarchical clustering: an overview', {\em Wiley
  Interdiscip. Rev. Data Min. Knowl. Discov.} {\bf 2},~86--97.

\harvarditem{Nelder \harvardand\ Wedderburn}{1972}{glm_1972}
Nelder, J.~A. \harvardand\ Wedderburn, R.~W.  \harvardyearleft
  1972\harvardyearright , `Generalized linear models', {\em Journal of the
  Royal Statistical Society: Series A (General)} {\bf 135}(3),~370--384.
\newblock Publisher: Wiley Online Library.

\harvarditem[Nowok et~al.]{Nowok, Raab \harvardand\ Dibben}{2016}{synthpop}
Nowok, B., Raab, G.~M. \harvardand\ Dibben, C.  \harvardyearleft
  2016\harvardyearright , `synthpop: {Bespoke} {Creation} of {Synthetic} {Data}
  in {R}', {\em Journal of Statistical Software} {\bf 74}(1),~1--26.
\newline\harvardurl{\url{https://www.jstatsoft.org/index.php/jss/article/view/v074i11}}

\harvarditem[Nußberger et~al.]{Nußberger, Boesel, Lenz, Binder \harvardand\
  Hess}{2020}{nussberger_synthetic_2020}
Nußberger, J., Boesel, F., Lenz, S., Binder, H. \harvardand\ Hess, M.
  \harvardyearleft 2020\harvardyearright , `Synthetic observations from deep
  generative models and binary omics data with limited sample size', {\em
  Briefings in Bioinformatics} .
\newline\harvardurl{\url{https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbaa226/5917048}}

\harvarditem[Oluwagbemigun et~al.]{Oluwagbemigun, Foerster, Watkins, Fouhy,
  Stanton, Bergmann, Boeing \harvardand\
  Nöthlings}{2020}{oluwagbemigun_datashield_2020}
Oluwagbemigun, K., Foerster, J., Watkins, C., Fouhy, F., Stanton, C., Bergmann,
  M.~M., Boeing, H. \harvardand\ Nöthlings, U.  \harvardyearleft
  2020\harvardyearright , `Dietary {Patterns} {Are} {Associated} with {Serum}
  {Metabolite} {Patterns} and {Their} {Association} {Is} {Influenced} by {Gut}
  {Bacteria} among {Older} {German} {Adults}', {\em The Journal of Nutrition}
  {\bf 150}(1),~149--158.
\newline\harvardurl{\url{https://doi.org/10.1093/jn/nxz194}}

\harvarditem[Pastorino et~al.]{Pastorino, Bishop, Crozier, Granström, Kordas,
  Küpers, O'Brien, Polanska, Sauder, Zafarmand, Wilson, Agyemang, Burton,
  Cooper, Corpeleijn, Dabelea, Hanke, Inskip, McAuliffe, Olsen, Vrijkotte,
  Brage, Kennedy, O'Gorman, Scherer, Wijndaele, Wareham, Desoye \harvardand\
  Ong}{2019}{pastorino_datashield_2019}
Pastorino, S., Bishop, T., Crozier, S.~R., Granström, C., Kordas, K., Küpers,
  L.~K., O'Brien, E.~C., Polanska, K., Sauder, K.~A., Zafarmand, M.~H., Wilson,
  R.~C., Agyemang, C., Burton, P.~R., Cooper, C., Corpeleijn, E., Dabelea, D.,
  Hanke, W., Inskip, H.~M., McAuliffe, F.~M., Olsen, S.~F., Vrijkotte, T.~G.,
  Brage, S., Kennedy, A., O'Gorman, D., Scherer, P., Wijndaele, K., Wareham,
  N.~J., Desoye, G. \harvardand\ Ong, K.~K.  \harvardyearleft
  2019\harvardyearright , `Associations between maternal physical activity in
  early and late pregnancy and offspring birth size: remote federated
  individual level meta-analysis from eight cohort studies', {\em BJOG: An
  International Journal of Obstetrics \& Gynaecology} {\bf 126}(4),~459--470.
\newline\harvardurl{\url{https://doi.org/10.1111/1471-0528.15542}}

\harvarditem[Paszke et~al.]{Paszke, Gross, Massa, Lerer, Bradbury, Chanan,
  Killeen, Lin, Gimelshein, Antiga, Desmaison, Kopf, Yang, DeVito, Raison,
  Tejani, Chilamkurthy, Steiner, Fang, Bai \harvardand\
  Chintala}{2019}{pytorch}
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen,
  T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E.,
  DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L.,
  Bai, J. \harvardand\ Chintala, S.  \harvardyearleft 2019\harvardyearright ,
  {PyTorch}: An imperative style, high-performance deep learning library, {\em
  in} H.~Wallach, H.~Larochelle, A.~Beygelzimer, F.~d\textquotesingle
  Alch\'{e}-Buc, E.~Fox \harvardand\ R.~Garnett, eds, `Advances in Neural
  Information Processing Systems 32', Curran Associates, Inc., pp.~8024--8035.
\newline\harvardurl{\url{https://proceedings.neurips.cc/paper/2019/file/bdbca288fee7f92f2bfa9f7012727740-Paper.pdf}}

\harvarditem[Pedregosa et~al.]{Pedregosa, Varoquaux, Gramfort, Michel, Thirion,
  Grisel, Blondel, Prettenhofer, Weiss, Dubourg, Vanderplas, Passos,
  Cournapeau, Brucher, Perrot \harvardand\ Duchesnay}{2011}{scikit-learn}
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
  O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
  Passos, A., Cournapeau, D., Brucher, M., Perrot, M. \harvardand\ Duchesnay,
  E.  \harvardyearleft 2011\harvardyearright , `Scikit-learn: Machine learning
  in {P}ython', {\em Journal of Machine Learning Research} {\bf
  12},~2825--2830.
\newline\harvardurl{\url{http://jmlr.org/papers/v12/pedregosa11a.html}}

\harvarditem{Postel}{1981}{tcpspec}
Postel, J.  \harvardyearleft 1981\harvardyearright , {\em Transmission
  {Control} {Protocol}}.
\newblock Library Catalog: tools.ietf.org.
\newline\harvardurl{\url{https://tools.ietf.org/html/rfc793}}

\harvarditem[Prokosch et~al.]{Prokosch, Acker, Bernarding, Binder, Boeker,
  Boerries, Daumke, Ganslandt, Hesser, Höning, Neumaier, Marquardt, Renz,
  Rothkötter, Schade-Brittinger, Schmücker, Schüttler, Sedlmayr, Serve,
  Sohrabi \harvardand\ Storf}{2018}{prokosch_miracum_2018}
Prokosch, H.-U., Acker, T., Bernarding, J., Binder, H., Boeker, M., Boerries,
  M., Daumke, P., Ganslandt, T., Hesser, J., Höning, G., Neumaier, M.,
  Marquardt, K., Renz, H., Rothkötter, H.-J., Schade-Brittinger, C.,
  Schmücker, P., Schüttler, J., Sedlmayr, M., Serve, H., Sohrabi, K.
  \harvardand\ Storf, H.  \harvardyearleft 2018\harvardyearright , `{MIRACUM}:
  {Medical} {Informatics} in {Research} and {Care} in {University} {Medicine}',
  {\em Methods of Information in Medicine} {\bf 57}(S 1),~e82--e91.
\newline\harvardurl{\url{http://www.thieme-connect.de/DOI/DOI?10.3414/ME17-02-0025}}

\harvarditem[Quick et~al.]{Quick, Holan \harvardand\
  Wikle}{2018}{quick_generating_2018}
Quick, H., Holan, S.~H. \harvardand\ Wikle, C.~K.  \harvardyearleft
  2018\harvardyearright , `Generating partially synthetic geocoded public use
  data with decreased disclosure risk by using differential smoothing', {\em
  Journal of the Royal Statistical Society: Series A (Statistics in Society)}
  {\bf 181}(3),~649--661.
\newline\harvardurl{\url{https://doi.org/10.1111/rssa.12360}}

\harvarditem[Quinn et~al.]{Quinn, Anthoff, Kamiński, Arakaki, Bouchet-Valat,
  Papp, Arslan, ExpandingMan, Revels, Schouten, Robinson, Ferris, Oskin,
  Sharma, Aluthge, Davies, Hanson, Kalybek, Lin, Dunn, Adenbaum, Day,
  Calderón, {Julia TagBot}, Samuel, Vertechi, Zwitch, Huttunen \harvardand\
  strickek}{2021}{tables.jl}
Quinn, J., Anthoff, D., Kamiński, B., Arakaki, T., Bouchet-Valat, M., Papp,
  T.~K., Arslan, A., ExpandingMan, Revels, J., Schouten, R., Robinson, N.,
  Ferris, A., Oskin, A., Sharma, A., Aluthge, D., Davies, E., Hanson, E.,
  Kalybek, E., Lin, I., Dunn, J., Adenbaum, J., Day, J., Calderón, J. B.~S.,
  {Julia TagBot}, Samuel, O., Vertechi, P., Zwitch, R., Huttunen, A.
  \harvardand\ strickek  \harvardyearleft 2021\harvardyearright ,
  `{JuliaData/Tables.jl}: An interface for tables in {Julia}'.
\newline\harvardurl{\url{https://doi.org/10.5281/zenodo.4682614}}

\harvarditem[Quinn et~al.]{Quinn, {{JuliaData} contributors} \harvardand\
  {Julia Computing, Inc.}}{2020}{juliacsvGithub}
Quinn, J., {{JuliaData} contributors} \harvardand\ {Julia Computing, Inc.}
  \harvardyearleft 2020\harvardyearright , `\proglang{Julia} package {CSV}
  ({GitHub} repository)'.
\newblock Version 0.8.4.
\newline\harvardurl{\url{https://github.com/JuliaData/CSV.jl}}

\harvarditem{{R Core Team}}{2018}{rAdmin}
{R Core Team}  \harvardyearleft 2018\harvardyearright , {\em \proglang{R}
  Installation and Administration}.
\newblock \proglang{R} version 3.6.3.
\newline\harvardurl{\url{https://cran.r-project.org/doc/manuals/r-release/R-admin.pdf}}

\harvarditem[Rajkomar et~al.]{Rajkomar, Dean \harvardand\
  Kohane}{2019}{machine_learning_review_nejm}
Rajkomar, A., Dean, J. \harvardand\ Kohane, I.  \harvardyearleft
  2019\harvardyearright , `Machine {Learning} in {Medicine}', {\em New England
  Journal of Medicine} {\bf 380}(14),~1347--1358.
\newline\harvardurl{\url{https://www.nejm.org/doi/full/10.1056/NEJMra1814259}}

\harvarditem[Ranzato et~al.]{Ranzato, Boureau, Chopra \harvardand\
  LeCun}{2007}{ranzato_ebm}
Ranzato, M., Boureau, Y.-L., Chopra, S. \harvardand\ LeCun, Y.
  \harvardyearleft 2007\harvardyearright , A unified energy-based framework for
  unsupervised learning, {\em in} `Artificial {Intelligence} and {Statistics}',
  pp.~371--379.

\harvarditem{{Regents of the University of California}}{1999}{bsd3}
{Regents of the University of California}  \harvardyearleft
  1999\harvardyearright , `The 3-{Clause} {BSD} {License}'.
\newline\harvardurl{\url{https://opensource.org/licenses/BSD-3-Clause}}

\harvarditem{{RStudio Team}}{2020}{rstudio}
{RStudio Team}  \harvardyearleft 2020\harvardyearright , {\em RStudio:
  Integrated Development Environment for R}, RStudio, PBC, Boston, MA.
\newline\harvardurl{\url{http://www.rstudio.com/}}

\harvarditem[Rumbaugh et~al.]{Rumbaugh, Jacobson \harvardand\ Booch}{1999}{uml}
Rumbaugh, J., Jacobson, I. \harvardand\ Booch, G.  \harvardyearleft
  1999\harvardyearright , {\em The unified modeling language reference manual},
  Addison-Wesley.

\harvarditem{Rumbold \harvardand\ Pierscionek}{2017}{rumbold_effect_2017}
Rumbold, J. M.~M. \harvardand\ Pierscionek, B.  \harvardyearleft
  2017\harvardyearright , `The {Effect} of the {General} {Data} {Protection}
  {Regulation} on {Medical} {Research}', {\em Journal of Medical Internet
  Research} {\bf 19}(2),~e7108.
\newline\harvardurl{\url{https://www.jmir.org/2017/2/e47}}

\harvarditem[Rumelhart et~al.]{Rumelhart, Hinton \harvardand\
  Williams}{1986}{backpropagation}
Rumelhart, D.~E., Hinton, G.~E. \harvardand\ Williams, R.~J.  \harvardyearleft
  1986\harvardyearright , `Learning representations by back-propagating
  errors', {\em Nature} {\bf 323}(6088),~533--536.
\newline\harvardurl{\url{https://www.nature.com/articles/323533a0}}

\harvarditem{Sagi \harvardand\ Rokach}{2018}{ensemble_learning_survey_2018}
Sagi, O. \harvardand\ Rokach, L.  \harvardyearleft 2018\harvardyearright ,
  `Ensemble learning: {A} survey', {\em {WIREs} Data Mining and Knowledge
  Discovery} {\bf 8}(4),~e1249.
\newline\harvardurl{\url{https://onlinelibrary.wiley.com/doi/abs/10.1002/widm.1249}}

\harvarditem{Salakhutdinov}{2008}{salakhutdinov2008learning}
Salakhutdinov, R.  \harvardyearleft 2008\harvardyearright , Learning and
  evaluating {Boltzmann} machines, Technical Report UTML TR 2008-002,
  Department of Computer Science, University of Toronto.
\newline\harvardurl{\url{http://www.cs.toronto.edu/~rsalakhu/papers/bm.pdf}}

\harvarditem{Salakhutdinov}{2015}{salakhutdinov2015generativemodels}
Salakhutdinov, R.  \harvardyearleft 2015\harvardyearright , `Learning deep
  generative models', {\em Annual Review of Statistics and Its Application}
  {\bf 2},~361--385.
\newline\harvardurl{\url{https://doi.org/10.1146/annurev-statistics-010814-020120}}

\harvarditem{Salakhutdinov \harvardand\ Hinton}{2009}{salakhutdinov2009DBMs}
Salakhutdinov, R. \harvardand\ Hinton, G.  \harvardyearleft
  2009\harvardyearright , Deep {Boltzmann} machines, {\em in} `Artificial
  Intelligence and Statistics', pp.~448--455.
\newline\harvardurl{\url{http://proceedings.mlr.press/v5/salakhutdinov09a.html}}

\harvarditem{Salakhutdinov \harvardand\ Hinton}{2012}{sala2012anefficient}
Salakhutdinov, R. \harvardand\ Hinton, G.  \harvardyearleft
  2012\harvardyearright , `An efficient learning procedure for deep {Boltzmann}
  machines', {\em Neural Computation} {\bf 24}(8),~1967--2006.
\newline\harvardurl{\url{http://doi.org/10.1162/NECO\_a\_00311}}

\harvarditem{Sammut \harvardand\ Webb}{2010}{ml_encyclopedia}
Sammut, C. \harvardand\ Webb, G.~I.  \harvardyearleft 2010\harvardyearright ,
  {\em Encyclopedia of {Machine} {Learning}}, Springer Science \& Business
  Media.

\harvarditem{Shabani \harvardand\
  Marelli}{2019}{shabani_re-identifiability_2019}
Shabani, M. \harvardand\ Marelli, L.  \harvardyearleft 2019\harvardyearright ,
  `Re-identifiability of genomic data and the {GDPR}', {\em EMBO reports} {\bf
  20}(6),~e48316.
\newblock Publisher: John Wiley \& Sons, Ltd.
\newline\harvardurl{\url{http://doi.org/10.15252/embr.201948316}}

\harvarditem{Smolensky}{1986}{smolensky1986foundations}
Smolensky, P.  \harvardyearleft 1986\harvardyearright , `Foundations of harmony
  theory: Cognitive dynamical systems and the subsymbolic theory of information
  processing', {\em Parallel distributed processing: Explorations in the
  microstructure of cognition} {\bf 1},~191--281.

\harvarditem[Sohn et~al.]{Sohn, Lee \harvardand\ Yan}{2015}{cvae}
Sohn, K., Lee, H. \harvardand\ Yan, X.  \harvardyearleft 2015\harvardyearright
  , Learning {Structured} {Output} {Representation} using {Deep} {Conditional}
  {Generative} {Models}, {\em in} C.~Cortes, N.~Lawrence, D.~Lee, M.~Sugiyama
  \harvardand\ R.~Garnett, eds, `Proceedings of the 28th International
  Conference on Neural Information Processing Systems - Volume 2', Vol.~28 of
  {\em NIPS'15}, MIT Press, Cambridge, MA, USA, p.~3483–3491.
\newline\harvardurl{\url{https://dl.acm.org/doi/abs/10.5555/2969442.2969628}}

\harvarditem{Srivastava \harvardand\
  Salakhutdinov}{2012}{srivastava2012multimodal}
Srivastava, N. \harvardand\ Salakhutdinov, R.~R.  \harvardyearleft
  2012\harvardyearright , Multimodal learning with deep {Boltzmann} machines,
  {\em in} F.~Pereira, C.~J.~C. Burges, L.~Bottou \harvardand\ K.~Q.
  Weinberger, eds, `Advances in neural information processing systems',
  Vol.~25, Curran Associates, Inc., pp.~2222--2230.
\newline\harvardurl{\url{https://proceedings.neurips.cc/paper/2012/file/af21d0c97db2e27e13572cbf59eb343d-Paper.pdf}}

\harvarditem{Sweeney}{2012}{sweeney_k_anonymity_2012}
Sweeney, L.  \harvardyearleft 2012\harvardyearright , `{k}-anonymity: A model
  for protecting privacy', {\em International Journal of Uncertainty, Fuzziness
  and Knowledge-Based Systems} .
\newblock Publisher: World Scientific Publishing Company.
\newline\harvardurl{\url{https://doi.org/10.1142/S0218488502001648}}

\harvarditem{{The 1000 Genomes Project Consortium}}{2012}{1000genomes}
{The 1000 Genomes Project Consortium}  \harvardyearleft 2012\harvardyearright ,
  `An integrated map of genetic variation from 1,092 human genomes', {\em
  Nature} {\bf 491}(7422),~56--65.
\newline\harvardurl{\url{http://dx.doi.org/10.1038/nature11632}}

\harvarditem{{The Theano Development Team}}{2016}{theano}
{The Theano Development Team}  \harvardyearleft 2016\harvardyearright ,
  `Theano: {A} {Python} framework for fast computation of mathematical
  expressions', {\em arXiv:1605.02688 [cs]} .
\newline\harvardurl{\url{http://arxiv.org/abs/1605.02688}}

\harvarditem{Theis}{2011}{deepbelief_github}
Theis, L.  \harvardyearleft 2011\harvardyearright , `Code for training and
  evaluating restricted boltzmann machines ({RBMs}) and deep belief networks
  ({DBNs})'.
\newline\harvardurl{\url{https://github.com/lucastheis/deepbelief}}

\harvarditem[Theis et~al.]{Theis, Gerwinn, Sinz \harvardand\
  Bethge}{2011}{theis2011deepbelief}
Theis, L., Gerwinn, S., Sinz, F. \harvardand\ Bethge, M.  \harvardyearleft
  2011\harvardyearright , `In all likelihood, deep belief is not enough', {\em
  Journal of Machine Learning Research} {\bf 12}(Nov),~3071--3096.
\newblock Associated code published on
  \url{https://github.com/lucastheis/deepbelief}.

\harvarditem[Theis et~al.]{Theis, Oord \harvardand\
  Bethge}{2015}{theis_note_2015}
Theis, L., Oord, A. v.~d. \harvardand\ Bethge, M.  \harvardyearleft
  2015\harvardyearright , `A note on the evaluation of generative models', {\em
  arXiv:1511.01844 [cs, stat]} .
\newblock arXiv: 1511.01844.
\newline\harvardurl{\url{http://arxiv.org/abs/1511.01844}}

\harvarditem[Toutouh et~al.]{Toutouh, Hemberg \harvardand\
  O'Reily}{2020}{toutouh_ensemblegan_2020}
Toutouh, J., Hemberg, E. \harvardand\ O'Reily, U.-M.  \harvardyearleft
  2020\harvardyearright , Re-purposing heterogeneous generative ensembles with
  evolutionary computation, {\em in} `Proceedings of the 2020 {Genetic} and
  {Evolutionary} {Computation} {Conference}', pp.~425--434.

\harvarditem[Treppner et~al.]{Treppner, Salas-Bastos, Hess, Lenz, Vogel
  \harvardand\ Binder}{2021}{treppner_making_2020}
Treppner, M., Salas-Bastos, A., Hess, M., Lenz, S., Vogel, T. \harvardand\
  Binder, H.  \harvardyearleft 2021\harvardyearright , `Synthetic single cell
  {RNA} sequencing data from small pilot studies using deep generative models',
  {\em Scientific Reports} {\bf 11}(1),~9403.
\newline\harvardurl{\url{http://doi.org/10.1038/s41598-021-88875-4}}

\harvarditem{van Buuren \harvardand\
  Groothuis-Oudshoorn}{2011}{mice_buuren_2011}
van Buuren, S. \harvardand\ Groothuis-Oudshoorn, K.  \harvardyearleft
  2011\harvardyearright , `mice: {Multivariate} {Imputation} by {Chained}
  {Equations} in {R}', {\em Journal of Statistical Software} {\bf
  45}(1),~1--67.
\newline\harvardurl{\url{https://www.jstatsoft.org/index.php/jss/article/view/v045i03}}

\harvarditem{Vlad}{2019}{performancegpucpu}
Vlad  \harvardyearleft 2019\harvardyearright , `Answer to: Training a simple
  model in {Tensorflow} {GPU} slower than {CPU}'.
\newblock Accessed 2021-03-23.
\newline\harvardurl{\url{https://stackoverflow.com/a/55750666/3180809}}

\harvarditem[Wang et~al.]{Wang, Ghasedi~Dizaji \harvardand\
  Huang}{2018}{wang_conditional_2018}
Wang, X., Ghasedi~Dizaji, K. \harvardand\ Huang, H.  \harvardyearleft
  2018\harvardyearright , `Conditional generative adversarial network for gene
  expression inference', {\em Bioinformatics} {\bf 34}(17),~i603--i611.
\newline\harvardurl{\url{https://doi.org/10.1093/bioinformatics/bty563}}

\harvarditem[Webster et~al.]{Webster, Rabin, Simon \harvardand\
  Jurie}{2019}{webster_detecting_2019}
Webster, R., Rabin, J., Simon, L. \harvardand\ Jurie, F.  \harvardyearleft
  2019\harvardyearright , Detecting {Overfitting} of {Deep} {Generative}
  {Networks} via {Latent} {Recovery}, {\em in} `2019 {IEEE}/{CVF} {Conference}
  on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})',
  pp.~11265--11274.
\newblock ISSN: 2575-7075.
\newline\harvardurl{\url{http://doi.org/10.1109/CVPR.2019.01153}}

\harvarditem{Wickham}{2016}{ggplot2}
Wickham, H.  \harvardyearleft 2016\harvardyearright , {\em ggplot2: Elegant
  Graphics for Data Analysis}, Springer-Verlag New York.
\newline\harvardurl{\url{https://ggplot2.tidyverse.org}}

\harvarditem[Wickham et~al.]{Wickham, François, { Henry} \harvardand\
  Müller}{2020}{dplyr}
Wickham, H., François, R., { Henry}, L. \harvardand\ Müller, K.
  \harvardyearleft 2020\harvardyearright , {\em dplyr: A Grammar of Data
  Manipulation}.
\newblock R package version 1.0.2.
\newline\harvardurl{\url{https://CRAN.R-project.org/package=dplyr}}

\harvarditem[Wolfson et~al.]{Wolfson, Wallace, Masca, Rowe, Sheehan, Ferretti,
  LaFlamme, Tobin, Macleod, Little, Fortier, Knoppers \harvardand\
  Burton}{2010}{wolfson_datashield}
Wolfson, M., Wallace, S.~E., Masca, N., Rowe, G., Sheehan, N.~A., Ferretti, V.,
  LaFlamme, P., Tobin, M.~D., Macleod, J., Little, J., Fortier, I., Knoppers,
  B.~M. \harvardand\ Burton, P.~R.  \harvardyearleft 2010\harvardyearright ,
  `{DataSHIELD}: resolving a conflict in contemporary bioscience—performing a
  pooled analysis of individual-level data without sharing the data', {\em
  International Journal of Epidemiology} {\bf 39}(5),~1372--1382.
\newline\harvardurl{\url{http://ije.oxfordjournals.org/content/39/5/1372}}

\harvarditem{Xianyi \harvardand\ Kroeker}{2020}{openblas}
Xianyi, Z. \harvardand\ Kroeker, M.  \harvardyearleft 2020\harvardyearright ,
  `{OpenBLAS}: {An} optimized {BLAS} library'.
\newline\harvardurl{\url{http://www.openblas.net/}}

\harvarditem{Ylonen \harvardand\ Lonvick}{2006}{ylonen_ssh}
Ylonen, T. \harvardand\ Lonvick, C.  \harvardyearleft 2006\harvardyearright ,
  {\em The {Secure} {Shell} ({SSH}) {Protocol} {Architecture}}.
\newblock Reqest for comments (RFC) 4251.
\newline\harvardurl{\url{https://www.rfc-editor.org/info/rfc4251}}

\harvarditem{Yuret}{2016}{knetjl}
Yuret, D.  \harvardyearleft 2016\harvardyearright , `{Knet} - {Koç}
  {University} deep learning framework for {Julia}'.
\newline\harvardurl{\url{https://github.com/denizyuret/Knet.jl}}

\harvarditem[Zappa~Nardelli et~al.]{Zappa~Nardelli, Belyakova, Pelenitsyn,
  Chung, Bezanson \harvardand\ Vitek}{2018}{zappa_nardelli_julia_2018}
Zappa~Nardelli, F., Belyakova, J., Pelenitsyn, A., Chung, B., Bezanson, J.
  \harvardand\ Vitek, J.  \harvardyearleft 2018\harvardyearright , `Julia
  subtyping: a rational reconstruction', {\em Proceedings of the ACM on
  Programming Languages} {\bf 2}(OOPSLA),~113:1--113:27.
\newline\harvardurl{\url{https://doi.org/10.1145/3276483}}

\harvarditem{Zhang}{2018}{mochajl}
Zhang, C.  \harvardyearleft 2018\harvardyearright , `{Mocha.jl} - deep learning
  framework for {Julia}'.
\newline\harvardurl{\url{https://github.com/pluskid/Mocha.jl}}

\end{thebibliography}