{"id":"https://openalex.org/W4312121135","doi":"https://doi.org/10.1145/3508352.3549347","title":"A Stochastic Approach to Handle Non-Determinism in Deep Learning-Based Design Rule Violation Predictions","display_name":"A Stochastic Approach to Handle Non-Determinism in Deep Learning-Based Design Rule Violation Predictions","publication_year":2022,"publication_date":"2022-10-30","ids":{"openalex":"https://openalex.org/W4312121135","doi":"https://doi.org/10.1145/3508352.3549347"},"language":"en","primary_location":{"id":"doi:10.1145/3508352.3549347","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3508352.3549347","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3508352.3549347","source":{"id":"https://openalex.org/S4363608844","display_name":"Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design","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":"Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3508352.3549347","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013528664","display_name":"Rongjian Liang","orcid":"https://orcid.org/0000-0001-8626-2359"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rongjian Liang","raw_affiliation_strings":["Texas A&amp;M University"],"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103235503","display_name":"Hua Xiang","orcid":"https://orcid.org/0000-0001-8920-9967"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hua Xiang","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101764248","display_name":"Jinwook Jung","orcid":"https://orcid.org/0000-0002-9384-5277"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinwook Jung","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103246390","display_name":"Jiang Hu","orcid":"https://orcid.org/0000-0003-1157-7799"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang Hu","raw_affiliation_strings":["Texas A&amp;M University"],"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043138186","display_name":"Gi-Joon Nam","orcid":"https://orcid.org/0000-0001-6355-2935"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gi-Joon Nam","raw_affiliation_strings":["IBM Research"],"affiliations":[{"raw_affiliation_string":"IBM Research","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5013528664"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2906,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.8015873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11159","display_name":"Manufacturing Process and Optimization","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/computer-science","display_name":"Computer science","score":0.6776275634765625},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6247085928916931},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5758873224258423},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5357199311256409},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5101459622383118},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.4581029415130615},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44771990180015564},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4362420439720154},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.349267840385437},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1657436192035675},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14011099934577942}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6776275634765625},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6247085928916931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5758873224258423},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5357199311256409},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5101459622383118},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.4581029415130615},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44771990180015564},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4362420439720154},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.349267840385437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1657436192035675},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14011099934577942},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3508352.3549347","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3508352.3549347","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3508352.3549347","source":{"id":"https://openalex.org/S4363608844","display_name":"Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design","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":"Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3508352.3549347","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3508352.3549347","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3508352.3549347","source":{"id":"https://openalex.org/S4363608844","display_name":"Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design","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":"Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3359949410","display_name":null,"funder_award_id":"GRC-CADT 3103.001","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"},{"id":"https://openalex.org/G7173670773","display_name":null,"funder_award_id":"CCF-2106725","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312121135.pdf","grobid_xml":"https://content.openalex.org/works/W4312121135.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1519516901","https://openalex.org/W1981890344","https://openalex.org/W2105616993","https://openalex.org/W2178873339","https://openalex.org/W2899885603","https://openalex.org/W2945582997","https://openalex.org/W2945706499","https://openalex.org/W2992137891","https://openalex.org/W3012124806","https://openalex.org/W3012412994","https://openalex.org/W4213262319"],"related_works":["https://openalex.org/W2081982437","https://openalex.org/W4394857231","https://openalex.org/W2027050655","https://openalex.org/W3028244590","https://openalex.org/W4254349500","https://openalex.org/W2014369232","https://openalex.org/W3122042562","https://openalex.org/W1964286703","https://openalex.org/W2169866437","https://openalex.org/W2115519811"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"is":[2],"a":[3,29],"promising":[4],"approach":[5,66],"to":[6,34,55],"early":[7],"DRV":[8,99],"(Design":[9],"Rule":[10],"Violation)":[11],"prediction.":[12],"However,":[13],"non-deterministic":[14],"parallel":[15],"routing":[16],"hampers":[17],"model":[18],"training":[19,86],"and":[20,50],"degrades":[21],"prediction":[22,101],"accuracy.":[23],"In":[24,38],"this":[25,36,39],"work,":[26],"we":[27,41],"propose":[28],"stochastic":[30],"approach,":[31,40],"called":[32],"LGC-Net,":[33],"solve":[35],"problem.":[37],"develop":[42],"new":[43],"techniques":[44],"of":[45,98],"Gaussian":[46,59],"random":[47],"field":[48],"layer":[49],"focal":[51],"likelihood":[52],"loss":[53],"function":[54],"seamlessly":[56],"integrate":[57],"Log":[58],"Cox":[60],"process":[61],"with":[62,77,84],"deep":[63],"learning.":[64],"This":[65],"provides":[67],"not":[68],"only":[69],"statistical":[70],"regression":[71],"results":[72,83],"but":[73],"also":[74],"classification":[75],"ones":[76],"different":[78],"thresholds":[79],"without":[80],"retraining.":[81],"Experimental":[82],"noisy":[85],"data":[87],"on":[88],"industrial":[89],"designs":[90],"demonstrate":[91],"that":[92],"LGC-Net":[93],"achieves":[94],"significantly":[95],"better":[96],"accuracy":[97],"density":[100],"than":[102],"prior":[103],"arts.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
