{"id":"https://openalex.org/W4205099615","doi":"https://doi.org/10.1109/bigdata52589.2021.9671346","title":"Enhanced Variational U-Net for Weather Forecasting","display_name":"Enhanced Variational U-Net for Weather Forecasting","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205099615","doi":"https://doi.org/10.1109/bigdata52589.2021.9671346"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671346","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671346","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5002273144","display_name":"Pak Hay Kwok","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pak Hay Kwok","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100406573","display_name":"Qi Qi","orcid":"https://orcid.org/0000-0001-9762-8838"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Qi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5002273144"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8602,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7904634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"5758","last_page":"5763"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9897000193595886,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/transfer-of-learning","display_name":"Transfer of learning","score":0.7553094625473022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6991996765136719},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6823740601539612},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.666611909866333},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6582885980606079},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.5503602623939514},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.5226457118988037},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.5136739611625671},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.498842716217041},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.496221125125885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4920610785484314},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41488102078437805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39896613359451294},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.21454259753227234},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18688547611236572},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13683608174324036},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13146671652793884},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1257743239402771},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08471262454986572}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7553094625473022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6991996765136719},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6823740601539612},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.666611909866333},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6582885980606079},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.5503602623939514},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.5226457118988037},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.5136739611625671},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.498842716217041},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.496221125125885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4920610785484314},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41488102078437805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39896613359451294},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.21454259753227234},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18688547611236572},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13683608174324036},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13146671652793884},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1257743239402771},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08471262454986572},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671346","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671346","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1936750108","https://openalex.org/W2963046541","https://openalex.org/W2963263347","https://openalex.org/W2963285578","https://openalex.org/W3196441873","https://openalex.org/W3209483374","https://openalex.org/W3213235731","https://openalex.org/W4226457101","https://openalex.org/W4250482878","https://openalex.org/W4297791576","https://openalex.org/W6685562342","https://openalex.org/W6726497184","https://openalex.org/W6752558437","https://openalex.org/W6755875945","https://openalex.org/W6800417461","https://openalex.org/W6803334366","https://openalex.org/W6803836949"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W3198847674","https://openalex.org/W3096913503"],"abstract_inverted_index":{"This":[0],"work":[1],"describes":[2],"our":[3,24],"third-place":[4],"solution":[5,21,76],"in":[6,26],"both":[7],"the":[8,34,41,51,55,69],"core":[9],"and":[10,32,60],"transfer":[11,66],"learning":[12,67],"challenges":[13],"of":[14,57],"Weather4cast":[15,27,45],"\u2013":[16],"IEEE":[17],"BigData":[18],"Cup.":[19],"The":[20,72],"builds":[22],"on":[23,40],"success":[25],"-":[28,46],"Stage":[29,47],"1":[30],"[1],":[31],"uses":[33],"same":[35],"Variational":[36],"U-Net":[37],"architecture.":[38],"Building":[39],"lessons":[42],"learned":[43],"from":[44],"1,":[48],"we":[49,64],"enhanced":[50],"model\u2019s":[52],"performance":[53],"through":[54],"use":[56],"data":[58],"augmentations":[59],"model":[61],"blending.":[62],"Furthermore,":[63],"explored":[65],"between":[68],"two":[70],"competitions.":[71],"code":[73],"for":[74],"this":[75],"is":[77],"available":[78],"at":[79],"https://github.com/qiq208/w4c-2021-IEEE":[80]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
