{"id":"https://openalex.org/W2766353659","doi":"https://doi.org/10.1109/aspdac.2018.8297385","title":"Spintronics based stochastic computing for efficient Bayesian inference system","display_name":"Spintronics based stochastic computing for efficient Bayesian inference system","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2766353659","doi":"https://doi.org/10.1109/aspdac.2018.8297385","mag":"2766353659"},"language":"en","primary_location":{"id":"doi:10.1109/aspdac.2018.8297385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aspdac.2018.8297385","pdf_url":null,"source":{"id":"https://openalex.org/S4363608266","display_name":"2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)","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":"2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)","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/A5101916099","display_name":"Xiaotao Jia","orcid":"https://orcid.org/0000-0003-2207-6092"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiaotao Jia","raw_affiliation_strings":["Fert Beijing Research Institute, BDBC, School of Electronic and Information Engineering"],"affiliations":[{"raw_affiliation_string":"Fert Beijing Research Institute, BDBC, School of Electronic and Information Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053303853","display_name":"Jianlei Yang","orcid":"https://orcid.org/0000-0001-8424-7040"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianlei Yang","raw_affiliation_strings":["Fert Beijing Research Institute, BDBC, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China"],"affiliations":[{"raw_affiliation_string":"Fert Beijing Research Institute, BDBC, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056897117","display_name":"Zhaohao Wang","orcid":"https://orcid.org/0000-0002-2999-7903"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaohao Wang","raw_affiliation_strings":["Fert Beijing Research Institute, BDBC, School of Electronic and Information Engineering"],"affiliations":[{"raw_affiliation_string":"Fert Beijing Research Institute, BDBC, School of Electronic and Information Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058073627","display_name":"Yiran Chen","orcid":"https://orcid.org/0000-0002-1486-8412"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiran Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, U.S.A","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429403","display_name":"Hai Li","orcid":"https://orcid.org/0000-0003-3228-6544"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hai Helen Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, U.S.A","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066473925","display_name":"Weisheng Zhao","orcid":"https://orcid.org/0000-0001-8088-0404"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weisheng Zhao","raw_affiliation_strings":["Fert Beijing Research Institute, BDBC, School of Electronic and Information Engineering"],"affiliations":[{"raw_affiliation_string":"Fert Beijing Research Institute, BDBC, School of Electronic and Information Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101916099"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.6807,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.96899066,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"580","last_page":"585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9976999759674072,"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.7256752252578735},{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.6489468812942505},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6337775588035583},{"id":"https://openalex.org/keywords/stochastic-computing","display_name":"Stochastic computing","score":0.5213964581489563},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4559619128704071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45368659496307373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4223475754261017},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.38933202624320984},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07880347967147827}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7256752252578735},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.6489468812942505},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6337775588035583},{"id":"https://openalex.org/C2780971903","wikidata":"https://www.wikidata.org/wiki/Q2933705","display_name":"Stochastic computing","level":3,"score":0.5213964581489563},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4559619128704071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45368659496307373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4223475754261017},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.38933202624320984},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07880347967147827}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aspdac.2018.8297385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aspdac.2018.8297385","pdf_url":null,"source":{"id":"https://openalex.org/S4363608266","display_name":"2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)","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":"2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1599534361","https://openalex.org/W1964242651","https://openalex.org/W1988580750","https://openalex.org/W2003056114","https://openalex.org/W2012117576","https://openalex.org/W2021453862","https://openalex.org/W2031267166","https://openalex.org/W2068896528","https://openalex.org/W2110276925","https://openalex.org/W2116676915","https://openalex.org/W2130894752","https://openalex.org/W2317199330","https://openalex.org/W2332482960","https://openalex.org/W2497735908","https://openalex.org/W2508890046","https://openalex.org/W2520217849","https://openalex.org/W2528070013","https://openalex.org/W2613124046","https://openalex.org/W2951786554","https://openalex.org/W3182208082","https://openalex.org/W6727242017"],"related_works":["https://openalex.org/W2944091050","https://openalex.org/W2998817056","https://openalex.org/W4221107656","https://openalex.org/W2904258669","https://openalex.org/W2077878098","https://openalex.org/W4313815718","https://openalex.org/W1506744765","https://openalex.org/W996380913","https://openalex.org/W2024084279","https://openalex.org/W4225555917"],"abstract_inverted_index":{"Bayesian":[0,34,75],"inference":[1,17,35,90,98],"is":[2,37,49,66],"an":[3,32],"effective":[4],"approach":[5,84],"for":[6],"solving":[7],"statistical":[8],"learning":[9],"problems":[10],"especially":[11],"with":[12],"uncertainty":[13],"and":[14,74,97],"incompleteness.":[15],"However,":[16],"efficiencies":[18,91],"are":[19],"physically":[20],"limited":[21],"by":[22,39,55,68],"the":[23,52,57,82],"bottlenecks":[24],"of":[25,60,71,94],"conventional":[26],"computing":[27],"platforms.":[28],"In":[29],"this":[30],"paper,":[31],"emerging":[33],"system":[36,65],"proposed":[38,64,83],"exploiting":[40],"spintronics":[41,61],"based":[42],"stochastic":[43,46],"computing.":[44],"A":[45],"bitstream":[47],"generator":[48],"realized":[50],"as":[51],"kernel":[53],"components":[54],"leveraging":[56],"inherent":[58],"randomness":[59],"devices.":[62],"The":[63],"evaluated":[67],"typical":[69],"applications":[70],"data":[72],"fusion":[73],"belief":[76],"networks.":[77],"Simulation":[78],"results":[79],"indicate":[80],"that":[81],"could":[85],"achieve":[86],"significant":[87],"improvement":[88],"on":[89],"in":[92],"terms":[93],"power":[95],"consumption":[96],"speed.":[99]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-01-14T23:40:02.550235","created_date":"2025-10-10T00:00:00"}
