{"id":"https://openalex.org/W2963870721","doi":"https://doi.org/10.1145/3292500.3330704","title":"Deep Uncertainty Quantification","display_name":"Deep Uncertainty Quantification","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2963870721","doi":"https://doi.org/10.1145/3292500.3330704","mag":"2963870721"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330704","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10453/141374","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100449066","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0001-5265-1030"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Bin Wang","raw_affiliation_strings":["University of Technology Sydney & Southwest Jiaotong University, Sydney, NB, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney & Southwest Jiaotong University, Sydney, NB, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100675577","display_name":"Jie L\u00fc","orcid":"https://orcid.org/0000-0003-0690-4732"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jie Lu","raw_affiliation_strings":["University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102936263","display_name":"Zheng Yan","orcid":"https://orcid.org/0000-0003-3368-2100"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zheng Yan","raw_affiliation_strings":["University of Technology Sydney, Centre for Artificial Intellig, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Centre for Artificial Intellig, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060295796","display_name":"Huaishao Luo","orcid":"https://orcid.org/0000-0003-4297-1270"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaishao Luo","raw_affiliation_strings":["Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Li","raw_affiliation_strings":["Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100681023","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0002-5224-4344"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["Xidian University & JD Intelligent Cities Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Xidian University & JD Intelligent Cities Research, Beijing, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062192039","display_name":"Guangquan Zhang","orcid":"https://orcid.org/0000-0003-3960-0583"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guangquan Zhang","raw_affiliation_strings":["University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100449066"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":6.1775,"has_fulltext":false,"cited_by_count":129,"citation_normalized_percentile":{"value":0.97237024,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2087","last_page":"2095"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/numerical-weather-prediction","display_name":"Numerical weather prediction","score":0.7196307182312012},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6734722852706909},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6516793966293335},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6157999634742737},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.608002781867981},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.5575342774391174},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5250815153121948},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.45273157954216003},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44599464535713196},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3490751385688782},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.320873498916626},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29596227407455444},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.25792330503463745},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19057318568229675},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.09992930293083191}],"concepts":[{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.7196307182312012},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6734722852706909},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6516793966293335},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6157999634742737},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.608002781867981},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.5575342774391174},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5250815153121948},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.45273157954216003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44599464535713196},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3490751385688782},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.320873498916626},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29596227407455444},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.25792330503463745},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19057318568229675},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.09992930293083191},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3292500.3330704","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/141374","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/141374","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"pmh:oai:opus.lib.uts.edu.au:123456789/141334","is_oa":false,"landing_page_url":"http://localhost:8080/xmlui/handle/123456789/141334","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/141374","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/141374","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G7091941409","display_name":null,"funder_award_id":"DP190101645","funder_id":"https://openalex.org/F4320337726","funder_display_name":"Centre of Excellence for Core to Crust Fluid Systems, Australian Research Council"},{"id":"https://openalex.org/G7922448862","display_name":null,"funder_award_id":"61773324, 61573292","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337726","display_name":"Centre of Excellence for Core to Crust Fluid Systems, Australian Research Council","ror":"https://ror.org/03nk9pp38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W582593712","https://openalex.org/W1485009520","https://openalex.org/W1545465591","https://openalex.org/W1560021816","https://openalex.org/W1560739766","https://openalex.org/W1979391944","https://openalex.org/W2001459659","https://openalex.org/W2002521620","https://openalex.org/W2008072410","https://openalex.org/W2013120098","https://openalex.org/W2082409570","https://openalex.org/W2082633923","https://openalex.org/W2095654324","https://openalex.org/W2112738128","https://openalex.org/W2116435618","https://openalex.org/W2137360132","https://openalex.org/W2171666055","https://openalex.org/W2172064003","https://openalex.org/W2417064059","https://openalex.org/W2469618837","https://openalex.org/W2788433952","https://openalex.org/W2809035759","https://openalex.org/W2898017895","https://openalex.org/W2915260006","https://openalex.org/W2950133940","https://openalex.org/W2963058055","https://openalex.org/W2963238274","https://openalex.org/W2964319113","https://openalex.org/W3102015031"],"related_works":["https://openalex.org/W3081577063","https://openalex.org/W3110237217","https://openalex.org/W4405031167","https://openalex.org/W2184710923","https://openalex.org/W3133000293","https://openalex.org/W3155716677","https://openalex.org/W2526518095","https://openalex.org/W2321020009","https://openalex.org/W4383218913","https://openalex.org/W4315472244"],"abstract_inverted_index":{"Weather":[0],"forecasting":[1,55,89],"is":[2,83,164],"usually":[3],"solved":[4],"through":[5],"numerical":[6],"weather":[7,54,124],"prediction":[8],"(NWP),":[9],"which":[10,93,163],"can":[11],"sometimes":[12],"lead":[13],"to":[14,18,40,96,109,141],"unsatisfactory":[15],"performance":[16],"due":[17],"inappropriate":[19],"setting":[20],"of":[21,79],"the":[22,53,133],"initial":[23],"states.":[24],"In":[25],"this":[26,156,169],"paper,":[27],"we":[28,94],"design":[29],"a":[30,68,119,165],"data-driven":[31],"method":[32,82],"augmented":[33],"by":[34,66,161],"an":[35,58],"effective":[36],"information":[37],"fusion":[38],"mechanism":[39],"learn":[41],"from":[42,49,123],"historical":[43],"data":[44],"that":[45,84,132],"incorporates":[46],"prior":[47],"knowledge":[48],"NWP.":[50],"We":[51],"cast":[52],"problem":[56,62],"as":[57,97],"end-to-end":[59],"deep":[60,98,103],"learning":[61],"and":[63,90,147],"solve":[64],"it":[65,85],"proposing":[67],"novel":[69],"negative":[70],"log-likelihood":[71],"error":[72,144,150],"(NLE)":[73],"loss":[74,136,146],"function.":[75],"A":[76],"notable":[77],"advantage":[78],"our":[80],"proposed":[81,134],"simultaneously":[86],"implements":[87],"single-value":[88],"uncertainty":[91,99],"quantification,":[92],"refer":[95],"quantification":[100],"(DUQ).":[101],"Efficient":[102],"ensemble":[104],"strategies":[105],"are":[106],"also":[107],"explored":[108],"further":[110],"improve":[111],"performance.":[112],"This":[113],"new":[114],"approach":[115,157],"was":[116],"evaluated":[117],"on":[118,168],"public":[120],"dataset":[121],"collected":[122],"stations":[125],"in":[126],"Beijing,":[127],"China.":[128],"Experimental":[129],"results":[130],"demonstrate":[131],"NLE":[135],"significantly":[137,158],"improves":[138,159],"generalization":[139],"compared":[140],"mean":[142,148],"squared":[143],"(MSE)":[145],"absolute":[149],"(MAE)":[151],"loss.":[152],"Compared":[153],"with":[154],"NWP,":[155],"accuracy":[160],"47.76%,":[162],"state-of-the-art":[166],"result":[167],"benchmark":[170],"dataset.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}