{"id":"https://openalex.org/W4280513650","doi":"https://doi.org/10.1109/tai.2022.3209167","title":"AutoKE: An Automatic Knowledge Embedding Framework for Scientific Machine Learning","display_name":"AutoKE: An Automatic Knowledge Embedding Framework for Scientific Machine Learning","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4280513650","doi":"https://doi.org/10.1109/tai.2022.3209167"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2022.3209167","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tai.2022.3209167","pdf_url":"https://ieeexplore.ieee.org/ielx7/9078688/9184921/09900391.pdf","source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/9078688/9184921/09900391.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072469433","display_name":"Mengge Du","orcid":"https://orcid.org/0000-0003-3987-9254"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengge Du","raw_affiliation_strings":["College of Engineering, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3987-9254","affiliations":[{"raw_affiliation_string":"College of Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101707444","display_name":"Yuntian Chen","orcid":"https://orcid.org/0000-0003-4566-8197"},"institutions":[{"id":"https://openalex.org/I4210138580","display_name":"Zhejiang Institute of Science and Technology Information","ror":"https://ror.org/04gq2fa58","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210138580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuntian Chen","raw_affiliation_strings":["Eastern Institute for Advanced Study, Yongriver Institute of Technology, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0003-4566-8197","affiliations":[{"raw_affiliation_string":"Eastern Institute for Advanced Study, Yongriver Institute of Technology, Zhejiang, China","institution_ids":["https://openalex.org/I4210138580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100783852","display_name":"Dongxiao Zhang","orcid":"https://orcid.org/0000-0001-6930-5994"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiao Zhang","raw_affiliation_strings":["National Center for Applied Mathematics Shenzhen (NCAMS), Southern University of Science and Technology, Guangdong, China","Department of Mathematics and Theories, Peng Cheng Laboratory, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-6930-5994","affiliations":[{"raw_affiliation_string":"National Center for Applied Mathematics Shenzhen (NCAMS), Southern University of Science and Technology, Guangdong, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I3045169105"]},{"raw_affiliation_string":"Department of Mathematics and Theories, Peng Cheng Laboratory, Guangdong, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":null,"fwci":1.7004,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.8385645,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"4","issue":"6","first_page":"1564","last_page":"1578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9927999973297119,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9865999817848206,"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/embedding","display_name":"Embedding","score":0.7062011361122131},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7000806331634521},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5558395385742188},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5504846572875977},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.5192787647247314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5120158791542053},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4425087571144104},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4353092610836029},{"id":"https://openalex.org/keywords/physical-law","display_name":"Physical law","score":0.43330809473991394},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.4242076873779297},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38645294308662415},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.15183821320533752}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7062011361122131},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7000806331634521},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5558395385742188},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5504846572875977},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.5192787647247314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5120158791542053},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4425087571144104},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4353092610836029},{"id":"https://openalex.org/C194583477","wikidata":"https://www.wikidata.org/wiki/Q408891","display_name":"Physical law","level":2,"score":0.43330809473991394},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.4242076873779297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38645294308662415},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.15183821320533752},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2022.3209167","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tai.2022.3209167","pdf_url":"https://ieeexplore.ieee.org/ielx7/9078688/9184921/09900391.pdf","source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tai.2022.3209167","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tai.2022.3209167","pdf_url":"https://ieeexplore.ieee.org/ielx7/9078688/9184921/09900391.pdf","source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2700625417","display_name":null,"funder_award_id":"ZDSYS20200421111201738","funder_id":"https://openalex.org/F4320327605","funder_display_name":"Southern University of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320327605","display_name":"Southern University of Science and Technology","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4280513650.pdf","grobid_xml":"https://content.openalex.org/works/W4280513650.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W844485810","https://openalex.org/W1968642437","https://openalex.org/W1975891294","https://openalex.org/W1979769287","https://openalex.org/W2051434435","https://openalex.org/W2104734313","https://openalex.org/W2110627003","https://openalex.org/W2114821552","https://openalex.org/W2256388387","https://openalex.org/W2899283552","https://openalex.org/W2899771611","https://openalex.org/W2908541468","https://openalex.org/W2946547492","https://openalex.org/W2962727772","https://openalex.org/W2963821229","https://openalex.org/W2969381807","https://openalex.org/W2990812820","https://openalex.org/W2995179471","https://openalex.org/W2999026783","https://openalex.org/W3006689658","https://openalex.org/W3010849941","https://openalex.org/W3011806874","https://openalex.org/W3014009018","https://openalex.org/W3014468003","https://openalex.org/W3016239339","https://openalex.org/W3021923779","https://openalex.org/W3037134996","https://openalex.org/W3041133507","https://openalex.org/W3041682155","https://openalex.org/W3080511210","https://openalex.org/W3082908155","https://openalex.org/W3084119156","https://openalex.org/W3104994177","https://openalex.org/W3112176480","https://openalex.org/W3112778626","https://openalex.org/W3128157635","https://openalex.org/W3163993681","https://openalex.org/W3202497309","https://openalex.org/W4200036085","https://openalex.org/W4223522428","https://openalex.org/W4255421341","https://openalex.org/W4281782255","https://openalex.org/W4287671439","https://openalex.org/W4386224308","https://openalex.org/W6631190155","https://openalex.org/W6638908295","https://openalex.org/W6713134421","https://openalex.org/W6752515464","https://openalex.org/W6756040250","https://openalex.org/W6758539823","https://openalex.org/W6771658506","https://openalex.org/W6783048280","https://openalex.org/W6800781246","https://openalex.org/W6810123564"],"related_works":["https://openalex.org/W3037664319","https://openalex.org/W2945599743","https://openalex.org/W3149970480","https://openalex.org/W1659546960","https://openalex.org/W2543363198","https://openalex.org/W4252762046","https://openalex.org/W1577064658","https://openalex.org/W170013976","https://openalex.org/W2386652184","https://openalex.org/W2903926864"],"abstract_inverted_index":{"Imposing":[0],"physical":[1,18,41,63,104,207,215],"constraints":[2],"on":[3],"neural":[4,96],"networks":[5,97],"as":[6,86],"a":[7,65,75,80,119,204],"method":[8],"of":[9,51,61,94,106,130,177,194,206],"knowledge":[10,216],"embedding":[11,62],"has":[12],"achieved":[13],"great":[14],"progress":[15],"in":[16,45,146,209],"solving":[17],"problems":[19,208,241],"described":[20],"by":[21,155,203],"governing":[22,29,82,135],"equations.":[23],"However,":[24],"for":[25,101],"many":[26],"engineering":[27],"problems,":[28],"equations":[30],"often":[31],"have":[32],"complex":[33,36,81,110],"forms,":[34],"including":[35],"partial":[37],"derivatives":[38],"or":[39],"stochastic":[40],"fields,":[42],"which":[43,210],"results":[44,224],"significant":[46],"inconveniences":[47],"from":[48],"the":[49,59,103,123,128,131,134,143,147,157,169,178,182,192,195,199,227],"perspective":[50],"implementation.":[52],"In":[53,89,197],"this":[54],"paper,":[55],"to":[56,133,171,181,190,239],"effectively":[57],"automate":[58],"process":[60],"knowledge,":[64],"scientific":[66],"machine":[67],"learning":[68,189],"framework,":[69],"called":[70],"AutoKE,":[71,90],"is":[72,84,99,137,165,201],"proposed,":[73],"and":[74,115,127],"reservoir":[76],"flow":[77],"problem":[78],"with":[79,152,242],"equation":[83,111,124,136],"taken":[85],"an":[87,91,173,218],"instance.":[88],"emulator":[92,132,179,219,228],"comprised":[93],"deep":[95],"(DNNs)":[98],"built":[100],"predicting":[102],"variables":[105],"interest.":[107],"An":[108],"arbitrarily":[109],"can":[112,212,229],"be":[113,237],"parsed":[114],"automatically":[116,213],"converted":[117],"into":[118,168,217],"computational":[120],"graph":[121],"through":[122],"parser":[125],"module,":[126],"fitness":[129],"evaluated":[138],"via":[139,245],"automatic":[140],"differentiation.":[141],"Furthermore,":[142],"fixed":[144],"weights":[145,154],"loss":[148],"function":[149],"are":[150],"substituted":[151],"adaptive":[153],"incorporating":[156],"Lagrangian":[158],"dual":[159],"method.":[160],"Neural":[161],"architecture":[162,176],"search":[163],"(NAS)":[164],"also":[166,236],"introduced":[167],"AutoKE":[170],"select":[172],"optimal":[174],"network":[175],"according":[180],"specific":[183],"problem.":[184],"Finally,":[185],"we":[186],"apply":[187],"transfer":[188,246],"enhance":[191],"scalability":[193],"emulator.":[196],"experiments,":[198],"framework":[200],"verified":[202],"series":[205],"it":[211],"embed":[214],"without":[220],"heavy":[221],"hand-coding.":[222],"The":[223],"demonstrate":[225],"that":[226],"not":[230],"only":[231],"make":[232],"accurate":[233],"predictions,":[234],"but":[235],"applied":[238],"similar":[240],"high":[243],"efficiency":[244],"learning.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}