{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:13:53Z","timestamp":1743142433615,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030983185"},{"type":"electronic","value":"9783030983192"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-98319-2_14","type":"book-chapter","created":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T07:03:13Z","timestamp":1653030193000},"page":"273-289","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Applications of Multivariate Quasi-Random Sampling with Neural Networks"],"prefix":"10.1007","author":[{"given":"Marius","family":"Hofert","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Avinash","family":"Prasad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,21]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity 31(3), 307\u2013327 (1986)","DOI":"10.1016\/0304-4076(86)90063-1"},{"key":"14_CR2","unstructured":"Dziugaite, G.K., Roy, D.M., Ghahramani, Z.: Training generative neural networks via maximum mean discrepancy optimization. In: Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, pp. 258\u2013267. AUAI Press (2015). http:\/\/www.auai.org\/uai2015\/proceedings\/papers\/230.pdf"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Embrechts, P., McNeil, A.J., Straumann, D.: Correlation and dependency in risk management: Properties and pitfalls. In: Dempster, M. (ed.) Risk Management: Value at Risk and Beyond, pp. 176\u2013223. Cambridge University Press, Cambridge (2002)","DOI":"10.1017\/CBO9780511615337.008"},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Genest, C., Segers, J.: On the covariance of the asymptotic empirical copula process 101(8), 1837\u20131845 (2010)","DOI":"10.1016\/j.jmva.2010.03.018"},{"key":"14_CR5","doi-asserted-by":"publisher","unstructured":"Hofert, M., Kojadinovic, I., Maechler, M., Yan, J.: Elements of Copula Modeling with R. Springer Use R! Series (2018). https:\/\/doi.org\/10.1007\/978-3-319-89635-9, http:\/\/www.springer.com\/de\/book\/9783319896342","DOI":"10.1007\/978-3-319-89635-9"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Hofert, M., Prasad, A., Zhu, M.: Quasi-random sampling for multivariate distributions via generative neural networks, pp. 1\u201324 (2021)","DOI":"10.1080\/10618600.2020.1868302"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Jondeau, E., Rockinger, M.: The copula-GARCH model of conditional dependencies: An international stock market application 25, 827\u2013853 (2006)","DOI":"10.1016\/j.jimonfin.2006.04.007"},{"key":"14_CR8","doi-asserted-by":"crossref","unstructured":"Lemieux, C.: Monte Carlo and Quasi\u2013Monte Carlo Sampling. Springer, Berlin (2009)","DOI":"10.1007\/978-0-387-78165-5_5"},{"key":"14_CR9","unstructured":"Li, Y., Swersky, K., Zemel, R.: Generative moment matching networks. In: International Conference on Machine Learning, pp. 1718\u20131727 (2015)"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Longstaff, F.A., Schwartz, E.S.: Valuing american options by simulation: a simple least-squares approach 14(1), 113\u2013147 (2001)","DOI":"10.1093\/rfs\/14.1.113"},{"key":"14_CR11","unstructured":"McNeil, A.J., Frey, R., Embrechts, P.: Quantitative Risk Management: Concepts, Techniques, Tools, 2 edn. Princeton University Press (2015)"},{"key":"14_CR12","unstructured":"Nelsen, R.B.: An Introduction to Copulas. Springer, Berlin (2006)"},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Patton, A.J.: Modelling asymmetric exchange rate dependence 47(2), 527\u2013556 (2006). http:\/\/public.econ.duke.edu\/~ap172\/Patton_IER_2006.pdf","DOI":"10.1111\/j.1468-2354.2006.00387.x"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"R\u00e9millard, B., Scaillet, O.: Testing for equality between two copulas 100(3), 377\u2013386 (2009)","DOI":"10.1016\/j.jmva.2008.05.004"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Scheuerer, M., Hamill, T.M.: Variogram-based proper scoring rules for probabilistic forecasts of multivariate quantities 143(4), 1321\u20131334 (2015)","DOI":"10.1175\/MWR-D-14-00269.1"},{"key":"14_CR16","unstructured":"Sklar, A.: Fonctions de r\u00e9partition \u00e0 n dimensions et leurs marges 8, 229\u2013231 (1959)"},{"key":"14_CR17","doi-asserted-by":"crossref","unstructured":"Weiss, A.: Arma models with arch errors 5(2), 129\u2013143 (1984)","DOI":"10.1111\/j.1467-9892.1984.tb00382.x"}],"container-title":["Springer Proceedings in Mathematics &amp; Statistics","Monte Carlo and Quasi-Monte Carlo Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-98319-2_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T07:05:33Z","timestamp":1653030333000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-98319-2_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030983185","9783030983192"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-98319-2_14","relation":{},"ISSN":["2194-1009","2194-1017"],"issn-type":[{"type":"print","value":"2194-1009"},{"type":"electronic","value":"2194-1017"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"21 May 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MCQMC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mcqmc2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mcqmc20.web.ox.ac.uk\/home","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}