{"id":"https://openalex.org/W4283808523","doi":"https://doi.org/10.3390/rs14133218","title":"Physics-Driven Deep Learning Inversion with Application to Magnetotelluric","display_name":"Physics-Driven Deep Learning Inversion with Application to Magnetotelluric","publication_year":2022,"publication_date":"2022-07-04","ids":{"openalex":"https://openalex.org/W4283808523","doi":"https://doi.org/10.3390/rs14133218"},"language":"en","primary_location":{"id":"doi:10.3390/rs14133218","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14133218","pdf_url":"https://www.mdpi.com/2072-4292/14/13/3218/pdf?version=1657072763","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/13/3218/pdf?version=1657072763","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058315243","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0003-1541-4153"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"],"raw_orcid":"https://orcid.org/0000-0003-1541-4153","affiliations":[{"raw_affiliation_string":"Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351633","display_name":"He Wang","orcid":"https://orcid.org/0000-0001-5283-0231"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Wang","raw_affiliation_strings":["Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114195592","display_name":"Zhenzhu Xi","orcid":"https://orcid.org/0000-0001-8239-9489"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenzhu Xi","raw_affiliation_strings":["Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695811","display_name":"Rongqing Zhang","orcid":"https://orcid.org/0000-0002-7871-9432"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongqing Zhang","raw_affiliation_strings":["Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072380374","display_name":"Xiaodi Huang","orcid":"https://orcid.org/0000-0002-6084-1851"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodi Huang","raw_affiliation_strings":["Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Ministry of Education), Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5114195592"],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":7.1742,"has_fulltext":true,"cited_by_count":53,"citation_normalized_percentile":{"value":0.98793498,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"14","issue":"13","first_page":"3218","last_page":"3218"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/occam","display_name":"occam","score":0.7458052039146423},{"id":"https://openalex.org/keywords/magnetotellurics","display_name":"Magnetotellurics","score":0.6890026330947876},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.6617896556854248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5726653337478638},{"id":"https://openalex.org/keywords/linearization","display_name":"Linearization","score":0.5400034189224243},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5351282954216003},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4489686191082001},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4226216971874237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39986109733581543},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.3762401342391968},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3393104672431946},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20756950974464417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14560467004776}],"concepts":[{"id":"https://openalex.org/C78469957","wikidata":"https://www.wikidata.org/wiki/Q838062","display_name":"occam","level":2,"score":0.7458052039146423},{"id":"https://openalex.org/C112313211","wikidata":"https://www.wikidata.org/wiki/Q1413106","display_name":"Magnetotellurics","level":3,"score":0.6890026330947876},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.6617896556854248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5726653337478638},{"id":"https://openalex.org/C11210021","wikidata":"https://www.wikidata.org/wiki/Q1520713","display_name":"Linearization","level":3,"score":0.5400034189224243},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5351282954216003},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4489686191082001},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4226216971874237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39986109733581543},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3762401342391968},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3393104672431946},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20756950974464417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14560467004776},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C69990965","wikidata":"https://www.wikidata.org/wiki/Q65402698","display_name":"Electrical resistivity and conductivity","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14133218","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14133218","pdf_url":"https://www.mdpi.com/2072-4292/14/13/3218/pdf?version=1657072763","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:48df42aa0de443daa72ef719360d4131","is_oa":true,"landing_page_url":"https://doaj.org/article/48df42aa0de443daa72ef719360d4131","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 13, p 3218 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/13/3218/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14133218","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 14; Issue 13; Pages: 3218","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14133218","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14133218","pdf_url":"https://www.mdpi.com/2072-4292/14/13/3218/pdf?version=1657072763","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2618960347","display_name":null,"funder_award_id":"41304090","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5545358997","display_name":null,"funder_award_id":"2016YFC0303104","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G563085543","display_name":null,"funder_award_id":"DY135-S1-1-07","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4283808523.pdf","grobid_xml":"https://content.openalex.org/works/W4283808523.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1973303079","https://openalex.org/W1975551669","https://openalex.org/W2013459156","https://openalex.org/W2021256246","https://openalex.org/W2086236003","https://openalex.org/W2098712263","https://openalex.org/W2108064160","https://openalex.org/W2108982325","https://openalex.org/W2133454905","https://openalex.org/W2142205121","https://openalex.org/W2511343645","https://openalex.org/W2607406448","https://openalex.org/W2776585113","https://openalex.org/W2810372792","https://openalex.org/W2899283552","https://openalex.org/W2906386705","https://openalex.org/W2968094316","https://openalex.org/W2980536111","https://openalex.org/W2983807332","https://openalex.org/W3047245470","https://openalex.org/W3093501093","https://openalex.org/W3101765447","https://openalex.org/W3127723726","https://openalex.org/W3138012559","https://openalex.org/W3159428095","https://openalex.org/W3195235709","https://openalex.org/W6640054144","https://openalex.org/W6687483927","https://openalex.org/W6795044316"],"related_works":["https://openalex.org/W2379471362","https://openalex.org/W2377084220","https://openalex.org/W2081467492","https://openalex.org/W2809693971","https://openalex.org/W2080106596","https://openalex.org/W2037493368","https://openalex.org/W3021715158","https://openalex.org/W2522016499","https://openalex.org/W2973208711","https://openalex.org/W2793448175"],"abstract_inverted_index":{"Due":[0],"to":[1,24,61,74,89,168,194,250],"the":[2,18,48,55,62,98,104,134,144,149,160,170,174,180,183,208,212,216,225,228,231,241,251,255,263,268,273],"strong":[3],"capability":[4],"of":[5,33,50,65,107,151,159,182,215,272],"building":[6],"complex":[7,197],"nonlinear":[8],"mapping":[9],"without":[10],"involving":[11],"linearization":[12],"theory":[13],"and":[14,67,79,88,121,164,187,202,220,230,254,270],"high":[15],"prediction":[16],"efficiency;":[17],"deep":[19,46],"learning":[20],"(DL)":[21],"technique":[22],"applied":[23],"solve":[25],"geophysical":[26],"inverse":[27,218],"problems":[28],"has":[29],"been":[30],"a":[31,77,115,124,153],"subject":[32],"growing":[34],"interest.":[35],"Currently,":[36],"most":[37],"DL-based":[38],"inversion":[39,128,235,247],"approaches":[40],"are":[41],"fully":[42,184],"data-driven":[43,117,161,185],"(namely":[44],"standard":[45],"learning),":[47],"performance":[49],"which":[51,266],"largely":[52],"depends":[53],"on":[54,97],"training":[56,81,146],"sample":[57],"sets.":[58],"However,":[59],"due":[60],"heavy":[63],"burden":[64],"time":[66],"computational":[68],"resources,":[69],"it":[70,193],"can":[71,210],"be":[72],"challenging":[73],"supply":[75],"such":[76],"massive":[78],"exhaustive":[80],"dataset":[82],"for":[83],"generic":[84],"realistic":[85,198],"exploration":[86,199],"scenarios":[87],"perform":[90],"network":[91,145,171],"training.":[92,172],"In":[93,131],"this":[94,132],"work,":[95],"based":[96],"recent":[99],"advances":[100],"in":[101,148],"physics-based":[102,165,189],"networks,":[103],"physical":[105,213],"laws":[106,214],"magnetotelluric":[108],"(MT)":[109],"wave":[110,139],"propagation":[111,140],"is":[112,141],"incorporated":[113],"into":[114,143],"purely":[116],"DL":[118,126,186],"approach":[119],"(PlainDNN)":[120],"thus":[122],"builds":[123],"physics-driven":[125],"MT":[127,138,217,258],"scheme":[129],"(PhyDNN).":[130],"scheme,":[133],"forward":[135],"operator":[136],"modeling":[137],"integrated":[142],"loop,":[147],"form":[150],"minimizing":[152],"hybrid":[154],"loss":[155],"objective":[156],"function":[157],"composed":[158],"model":[162],"misfit":[163],"data":[166],"misfit,":[167],"guide":[169],"Consequently,":[173],"proposed":[175],"PhyDNN":[176,209,226,242,274],"method":[177,243],"will":[178],"take":[179],"advantage":[181],"conventional":[188],"deterministic":[190,233],"methods,":[191],"allowing":[192],"deal":[195],"with":[196,221,262],"scenarios.":[200],"Quantitative":[201],"qualitative":[203],"analysis":[204],"results":[205,248],"demonstrate":[206],"that":[207],"honor":[211],"problem,":[219],"other":[222],"conditions":[223],"unchanged,":[224],"outperforms":[227],"PlainDNN":[229],"classical":[232],"Occam":[234,252],"method.":[236,275],"When":[237],"processing":[238],"field":[239],"data,":[240],"yields":[244],"considerably":[245],"impressive":[246],"compared":[249],"method,":[253],"corresponding":[256],"simulated":[257],"responses":[259],"agree":[260],"well":[261],"real":[264],"measurements,":[265],"confirms":[267],"effectiveness":[269],"applicability":[271]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2022-07-06T00:00:00"}