Gaussian process emulation for exploring complex infectious disease models.
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| Title: | Gaussian process emulation for exploring complex infectious disease models. |
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| 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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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1013849 |
