{"id":"https://openalex.org/W7162659105","doi":"https://doi.org/10.1109/isqed69900.2026.11534754","title":"Data Augmentation Strategies for Machine Learning-based Compact Modeling of Emerging Devices","display_name":"Data Augmentation Strategies for Machine Learning-based Compact Modeling of Emerging Devices","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7162659105","doi":"https://doi.org/10.1109/isqed69900.2026.11534754"},"language":null,"primary_location":{"id":"doi:10.1109/isqed69900.2026.11534754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed69900.2026.11534754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 27th International Symposium on Quality Electronic Design (ISQED)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5042017268","display_name":"Diego Ferrer","orcid":"https://orcid.org/0000-0002-5993-1366"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diego Ferrer","raw_affiliation_strings":["The University of Tennessee,Knoxville,TN,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tennessee,Knoxville,TN,USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101904176","display_name":"Md. Mazharul Islam","orcid":"https://orcid.org/0000-0002-0853-6673"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md. Mazharul Islam","raw_affiliation_strings":["The University of Tennessee,Knoxville,TN,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tennessee,Knoxville,TN,USA","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735913","display_name":"Wei Pan","orcid":"https://orcid.org/0000-0002-8807-8974"},"institutions":[{"id":"https://openalex.org/I192454743","display_name":"Sandia National Laboratories California","ror":"https://ror.org/058m7ey48","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I1330989302","https://openalex.org/I192454743","https://openalex.org/I198811213","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Pan","raw_affiliation_strings":["Sandia National Laboratories,Livermore,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories,Livermore,CA,USA","institution_ids":["https://openalex.org/I192454743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137290311","display_name":"Juan P. Mendez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juan P. Mendez","raw_affiliation_strings":["Sandia National Laboratories,Albuquerque,NM,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories,Albuquerque,NM,USA","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137291418","display_name":"Denis Malamuy","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Denis Malamuy","raw_affiliation_strings":["Sandia National Laboratories,Albuquerque,NM,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sandia National Laboratories,Albuquerque,NM,USA","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137256896","display_name":"Ahmedullah Aziz","orcid":null},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmedullah Aziz","raw_affiliation_strings":["The University of Tennessee,Knoxville,TN,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tennessee,Knoxville,TN,USA","institution_ids":["https://openalex.org/I75027704"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.07880000025033951,"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":0.07880000025033951,"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/T14347","display_name":"Big Data and Digital Economy","score":0.03550000116229057,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.0333000011742115,"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/key","display_name":"Key (lock)","score":0.3142000138759613},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.27000001072883606},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.2653999924659729},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.2597000002861023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5651999711990356},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2992999851703644},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25040000677108765},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.24729999899864197},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.2379000037908554}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isqed69900.2026.11534754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isqed69900.2026.11534754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 27th International Symposium on Quality Electronic Design (ISQED)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4542297124862671}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1863606698","https://openalex.org/W2062760225","https://openalex.org/W2537883087","https://openalex.org/W2618530766","https://openalex.org/W2767106145","https://openalex.org/W2803444129","https://openalex.org/W2895175378","https://openalex.org/W2954996726","https://openalex.org/W3182706339","https://openalex.org/W4226538822","https://openalex.org/W4286470482","https://openalex.org/W4308885876","https://openalex.org/W4312875279","https://openalex.org/W4382940963","https://openalex.org/W4386763568","https://openalex.org/W4390614276","https://openalex.org/W4391559877","https://openalex.org/W4392880160","https://openalex.org/W4402835625","https://openalex.org/W4402861010","https://openalex.org/W4405185416","https://openalex.org/W4406882106","https://openalex.org/W4414988661","https://openalex.org/W4415302755","https://openalex.org/W4415482534","https://openalex.org/W7117469064"],"related_works":[],"abstract_inverted_index":{"In":[0,52],"this":[1,53],"paper,":[2],"we":[3,55,90],"demonstrate":[4],"two":[5],"novel":[6],"data":[7,33,103,121,126],"augmentation":[8],"methods":[9,30,58],"designed":[10],"to":[11,46,122,147],"enable":[12],"the":[13,39,60,68,124,141,144],"training":[14,148],"of":[15,38,62,100,118,143],"a":[16,48,98,116],"ML-based":[17,49,64],"compact":[18,50,65],"model":[19,66,145],"for":[20,67,88,128],"an":[21,63,75],"emerging":[22,76],"device":[23,78],"with":[24,79],"extremely":[25],"limited":[26],"experimental":[27,84,125,151],"data.":[28,152],"These":[29],"address":[31],"sparse":[32],"and":[34,109,111,138],"class":[35],"imbalance,":[36],"some":[37],"most":[40],"difficult":[41],"challenges":[42],"faced":[43],"when":[44],"trying":[45],"create":[47],"model.":[51],"work,":[54],"apply":[56],"these":[57],"in":[59,134],"creation":[61],"quantum-enhanced":[69,77],"Josephson":[70],"Junction":[71],"Field":[72],"Effect":[73],"Transistor,":[74],"substantial":[80],"potential":[81],"but":[82],"scarce":[83],"characterization.":[85],"To":[86],"account":[87],"this,":[89],"developed":[91],"Dynamic":[92],"Gaussian":[93],"Noise":[94],"Data":[95,113],"Augmentation":[96],"(DGNDA),":[97],"method":[99,117],"generating":[101],"additional":[102],"points":[104],"using":[105,119],"those":[106],"already":[107],"available,":[108],"Experimental":[110],"Simulation":[112],"Mixing":[114],"(ESDM),":[115],"simulation":[120],"augment":[123],"used":[127],"training.":[129],"DGNDA":[130],"demonstrated":[131],"strengthened":[132],"accuracy":[133,142],"modeling":[135],"underrepresented":[136],"classes":[137],"ESDM":[139],"maintained":[140],"comparable":[146],"exclusively":[149],"on":[150]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-05-29T00:00:00"}