{"id":"https://openalex.org/W3100250056","doi":"https://doi.org/10.1080/00207721.2020.1838663","title":"Altering Gaussian process to Student-<i>t</i> process for maximum distribution construction","display_name":"Altering Gaussian process to Student-<i>t</i> process for maximum distribution construction","publication_year":2020,"publication_date":"2020-11-10","ids":{"openalex":"https://openalex.org/W3100250056","doi":"https://doi.org/10.1080/00207721.2020.1838663","mag":"3100250056"},"language":"en","primary_location":{"id":"doi:10.1080/00207721.2020.1838663","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207721.2020.1838663","pdf_url":null,"source":{"id":"https://openalex.org/S129640837","display_name":"International Journal of Systems Science","issn_l":"0020-7721","issn":["0020-7721","1464-5319"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Systems Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100432937","display_name":"Weidong Wang","orcid":"https://orcid.org/0000-0002-7772-6817"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weidong Wang","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, People\u2019s Republic of China","School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, People\u2019s Republic of China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029806909","display_name":"Qin Yu","orcid":"https://orcid.org/0000-0001-6379-9444"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Yu","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, People\u2019s Republic of China","School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, People\u2019s Republic of China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021136553","display_name":"Maria Fasli","orcid":"https://orcid.org/0000-0001-8831-102X"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maria Fasli","raw_affiliation_strings":["Institute for Data Analytics and Science, School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Data Analytics and Science, School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK","institution_ids":["https://openalex.org/I110002522"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100432937"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.2608,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64548821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"52","issue":"4","first_page":"727","last_page":"755"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6253518462181091},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5375162959098816},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5362427234649658},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5222459435462952},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5035874247550964},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4685657322406769},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.46240976452827454},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4563409090042114},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.42928123474121094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4230012893676758},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.41066625714302063},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3798307180404663},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3682191073894501},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3230974078178406},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25885114073753357},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2531340718269348}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6253518462181091},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5375162959098816},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5362427234649658},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5222459435462952},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5035874247550964},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4685657322406769},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.46240976452827454},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4563409090042114},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.42928123474121094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4230012893676758},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.41066625714302063},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3798307180404663},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3682191073894501},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3230974078178406},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25885114073753357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2531340718269348},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/00207721.2020.1838663","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00207721.2020.1838663","pdf_url":null,"source":{"id":"https://openalex.org/S129640837","display_name":"International Journal of Systems Science","issn_l":"0020-7721","issn":["0020-7721","1464-5319"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Systems Science","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:taf:tsysxx:v:52:y:2021:i:4:p:727-755","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/00207721.2020.1838663","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5056992982","display_name":"\u57fa\u4e8e\u4e2d\u7ee7\u7684\u6570\u80fd\u4e00\u4f53\u5316\u7f51\u7edc\u90e8\u7f72\u53ca\u8d44\u6e90\u5206\u914d\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61871076","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7368362902","display_name":null,"funder_award_id":"ES/S007156/1","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"},{"id":"https://openalex.org/G8322284704","display_name":null,"funder_award_id":"ES/L011859/1","funder_id":"https://openalex.org/F4320334630","funder_display_name":"Economic and Social Research Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334630","display_name":"Economic and Social Research Council","ror":"https://ror.org/03n0ht308"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W95577512","https://openalex.org/W178169250","https://openalex.org/W1502922572","https://openalex.org/W1506859583","https://openalex.org/W1532345238","https://openalex.org/W1693986406","https://openalex.org/W1906251583","https://openalex.org/W2025207305","https://openalex.org/W2040731319","https://openalex.org/W2061144551","https://openalex.org/W2098613108","https://openalex.org/W2099201756","https://openalex.org/W2112036188","https://openalex.org/W2113741278","https://openalex.org/W2144533338","https://openalex.org/W2192203593","https://openalex.org/W2229155352","https://openalex.org/W2317988884","https://openalex.org/W2402392025","https://openalex.org/W2408565094","https://openalex.org/W2466409304","https://openalex.org/W2490431186","https://openalex.org/W2502413627","https://openalex.org/W2560674852","https://openalex.org/W2594579511","https://openalex.org/W2595982264","https://openalex.org/W2735731743","https://openalex.org/W2740772560","https://openalex.org/W2781685589","https://openalex.org/W2786022758","https://openalex.org/W2787502244","https://openalex.org/W2793908792","https://openalex.org/W2889833395","https://openalex.org/W2895133117","https://openalex.org/W2963697351","https://openalex.org/W2963930274","https://openalex.org/W3099840345","https://openalex.org/W3100723973","https://openalex.org/W3106144028","https://openalex.org/W4236876623"],"related_works":["https://openalex.org/W2141609920","https://openalex.org/W2562263695","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W2912851808","https://openalex.org/W4294619368","https://openalex.org/W4380558509"],"abstract_inverted_index":{"Gaussian":[0],"process":[1,160],"(GP)":[2],"regression":[3,76],"is":[4,27,47,66,83,133],"widely":[5],"used":[6],"to":[7,135,144,187],"find":[8],"the":[9,41,44,62,87,98,108,115,137,145,152,156,167,177,188],"extreme":[10,42],"of":[11,43,94,100,117,158],"a":[12,32,49,53,91,128,184],"black-box":[13],"function":[14,20,46,82,102],"by":[15,30,78,114],"iteratively":[16],"approximating":[17],"an":[18,80],"objective":[19,45],"when":[21],"new":[22],"evaluation":[23,26],"obtained.":[24],"Such":[25],"usually":[28],"made":[29,107],"optimising":[31,79],"given":[33],"acquisition":[34,81,101],"function.":[35],"However,":[36],"for":[37],"non-parametric":[38],"Bayesian":[39,126],"optimisation,":[40,127],"not":[48],"deterministic":[50],"value,":[51],"but":[52],"random":[54],"variant":[55],"with":[56,140],"distribution.":[57],"We":[58],"call":[59],"such":[60,71],"distribution":[61,64,139,154,182],"maximum":[63,72,138,153,181],"which":[65,106,162],"generally":[67],"non-analytical.":[68],"To":[69],"construct":[70,151],"distribution,":[73],"traditional":[74],"GP":[75,88,148],"method":[77,121,132,146],"computational":[84],"cost":[85],"as":[86],"model":[89],"has":[90,183],"cubic":[92],"computation":[93],"training":[95,168],"data.":[96,169],"Moreover,":[97],"introduction":[99],"brings":[103],"extra":[104],"hyperparameters":[105],"optimisation":[109],"more":[110,164],"complicated.":[111],"Recently,":[112],"inspired":[113],"idea":[116],"Sequential":[118],"Monte":[119,129,179],"Carlo":[120,130,180],"and":[122,172],"its":[123],"application":[124],"in":[125],"alike":[131],"proposed":[134],"approximate":[136],"weighted":[141],"samples.":[142],"Alternative":[143],"on":[147],"model,":[149],"we":[150],"within":[155],"framework":[157],"Student-t":[159],"(TP)":[161],"considers":[163],"uncertainties":[165],"from":[166],"Toy":[170],"examples":[171],"real":[173],"data":[174],"experiment":[175],"show":[176],"TP-based":[178],"competitive":[185],"performance":[186],"GP-based":[189],"method.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}