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Gaussian process emulation for exploring complex infectious disease models.

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Title: Gaussian process emulation for exploring complex infectious disease models.
Authors: Langmüller AM; Department of Computational Biology, Cornell University, Ithaca, New York, United States of America.; Department of Mathematics, University of Vienna, Vienna, Austria.; Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark., Chandrasekher KA; Department of Computational Biology, Cornell University, Ithaca, New York, United States of America., Haller BC; Department of Computational Biology, Cornell University, Ithaca, New York, United States of America., Champer SE; Department of Computational Biology, Cornell University, Ithaca, New York, United States of America., Murdock CC; Department of Entomology, Cornell University, Ithaca, New York, United States of America.; Cornell Institute of Host-Microbe Interactions and Disease, Cornell University, Ithaca, New York, United States of America.; Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America., Messer PW; Department of Computational Biology, Cornell University, Ithaca, New York, United States of America.
Source: PLoS computational biology [PLoS Comput Biol] 2025 Dec 29; Vol. 21 (12), pp. e1013849. Date of Electronic Publication: 2025 Dec 29 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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