{"id":"https://openalex.org/W4408563941","doi":"https://doi.org/10.1109/tcsi.2025.3543065","title":"Bayes2IMC: In-Memory Computing for Bayesian Binary Neural Networks","display_name":"Bayes2IMC: In-Memory Computing for Bayesian Binary Neural Networks","publication_year":2025,"publication_date":"2025-03-18","ids":{"openalex":"https://openalex.org/W4408563941","doi":"https://doi.org/10.1109/tcsi.2025.3543065"},"language":"en","primary_location":{"id":"doi:10.1109/tcsi.2025.3543065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2025.3543065","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Circuits and Systems I: Regular Papers","raw_type":"journal-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/A5076449772","display_name":"Prabodh Katti","orcid":"https://orcid.org/0000-0003-1919-9593"},"institutions":[{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Prabodh Katti","raw_affiliation_strings":["Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1919-9593","affiliations":[{"raw_affiliation_string":"Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K","institution_ids":["https://openalex.org/I4210119896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052256139","display_name":"Cl\u00e9ment Ruah","orcid":"https://orcid.org/0000-0001-8635-9943"},"institutions":[{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Clement Ruah","raw_affiliation_strings":["Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0001-8635-9943","affiliations":[{"raw_affiliation_string":"Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K","institution_ids":["https://openalex.org/I4210119896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017736224","display_name":"Osvaldo Simeone","orcid":"https://orcid.org/0000-0001-9898-3209"},"institutions":[{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Osvaldo Simeone","raw_affiliation_strings":["Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0001-9898-3209","affiliations":[{"raw_affiliation_string":"Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K","institution_ids":["https://openalex.org/I4210119896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012783672","display_name":"Bashir M. Al\u2010Hashimi","orcid":"https://orcid.org/0000-0002-3591-1328"},"institutions":[{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bashir M. Al-Hashimi","raw_affiliation_strings":["Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0002-3591-1328","affiliations":[{"raw_affiliation_string":"Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K","institution_ids":["https://openalex.org/I4210119896"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048595299","display_name":"Bipin Rajendran","orcid":"https://orcid.org/0000-0002-2960-6909"},"institutions":[{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bipin Rajendran","raw_affiliation_strings":["Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Centre for Intelligent Information Processing Systems (CIIPS), King&#x2019;s College London, London, U.K","institution_ids":["https://openalex.org/I4210119896"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5175,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.92021566,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"72","issue":"10","first_page":"5422","last_page":"5435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9926999807357788,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9926999807357788,"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/T12676","display_name":"Machine Learning and ELM","score":0.9399999976158142,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9352999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6733106374740601},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5709318518638611},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4976334869861603},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4836095869541168},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33780020475387573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2931509017944336},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20982396602630615},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.14503422379493713}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6733106374740601},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5709318518638611},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4976334869861603},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4836095869541168},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33780020475387573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2931509017944336},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20982396602630615},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.14503422379493713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsi.2025.3543065","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsi.2025.3543065","pdf_url":null,"source":{"id":"https://openalex.org/S116977442","display_name":"IEEE Transactions on Circuits and Systems I Regular Papers","issn_l":"1549-8328","issn":["1549-8328","1558-0806"],"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 Circuits and Systems I: Regular Papers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5419401992","display_name":"FreeML: Engineering Networked Machine Learning via Meta-Free Energy Minimisation","funder_award_id":"EP/W024101/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8699128427","display_name":"ECCS-EPSRC: NeuroComm: Brain-Inspired Wireless Communications -- From Theoretical Foundations to Implementation for 6G and Beyond","funder_award_id":"EP/X011852/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W2022639263","https://openalex.org/W2122352981","https://openalex.org/W2269491305","https://openalex.org/W2325850497","https://openalex.org/W2526202524","https://openalex.org/W2588191434","https://openalex.org/W2775637085","https://openalex.org/W2785466952","https://openalex.org/W2897686304","https://openalex.org/W2948661249","https://openalex.org/W2953352640","https://openalex.org/W2960778947","https://openalex.org/W2972862238","https://openalex.org/W2980034233","https://openalex.org/W2987612038","https://openalex.org/W3005619596","https://openalex.org/W3022634314","https://openalex.org/W3036450648","https://openalex.org/W3043426275","https://openalex.org/W3125908175","https://openalex.org/W3134244351","https://openalex.org/W3139521791","https://openalex.org/W3152980481","https://openalex.org/W3155456425","https://openalex.org/W3157454667","https://openalex.org/W3183264033","https://openalex.org/W3185425515","https://openalex.org/W3197327073","https://openalex.org/W3201362361","https://openalex.org/W3211621070","https://openalex.org/W4226192365","https://openalex.org/W4251999575","https://openalex.org/W4285144887","https://openalex.org/W4292169167","https://openalex.org/W4317927903","https://openalex.org/W4319068960","https://openalex.org/W4385245195","https://openalex.org/W4387350479","https://openalex.org/W4388822849","https://openalex.org/W4392367648","https://openalex.org/W4394827161","https://openalex.org/W4400231467"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Bayesian":[0,29],"Neural":[1],"Networks":[2],"(BNNs)":[3],"generate":[4,41],"an":[5,52,166],"ensemble":[6],"of":[7,24,116,119,126,212],"possible":[8],"models":[9],"by":[10],"treating":[11],"model":[12,44,136],"weights":[13],"as":[14,35,109,111],"random":[15],"variables.":[16],"This":[17],"enables":[18],"them":[19],"to":[20,40,66,100,112,145,173,191,225,231],"provide":[21],"superior":[22],"estimates":[23],"decision":[25],"uncertainty.":[26],"However,":[27],"implementing":[28],"inference":[30],"in":[31,183,201,220],"hardware":[32,210],"is":[33],"resource-intensive,":[34],"it":[36],"requires":[37],"noise":[38],"sources":[39],"the":[42,63,80,87,114,124,130,208,221,232],"desired":[43],"weights.":[45],"In":[46,206],"this":[47],"work,":[48],"we":[49],"introduce":[50],"Bayes2IMC,":[51],"in-memory":[53],"computing":[54],"(IMC)":[55],"architecture":[56],"designed":[57],"for":[58,82],"binary":[59],"BNNs":[60],"that":[61],"leverages":[62],"stochasticity":[64],"inherent":[65],"nanoscale":[67],"devices.":[68,121],"Our":[69],"novel":[70],"design,":[71],"based":[72],"on":[73,107,129],"Phase-Change":[74],"Memory":[75],"(PCM)":[76],"crossbar":[77],"arrays":[78],"eliminates":[79],"necessity":[81],"Analog-to-Digital":[83],"Converter":[84],"(ADC)":[85],"within":[86],"array,":[88],"significantly":[89],"improving":[90],"power":[91,202,228],"and":[92,156,162,188],"area":[93,163],"efficiency.":[94],"Hardware-software":[95],"co-optimized":[96],"corrections":[97],"are":[98],"introduced":[99],"reduce":[101],"device-induced":[102],"accuracy":[103,142],"variations":[104],"across":[105],"deployments":[106],"hardware,":[108],"well":[110],"mitigate":[113],"effect":[115],"conductance":[117],"drift":[118],"PCM":[120],"We":[122,149],"validate":[123],"effectiveness":[125],"our":[127],"approach":[128],"CIFAR-10":[131],"dataset":[132],"with":[133],"a":[134,152,171,189],"VGGBinaryConnect":[135],"containing":[137],"14":[138],"million":[139],"parameters,":[140],"achieving":[141,223],"metrics":[143],"comparable":[144],"ideal":[146],"software":[147],"implementations.":[148],"also":[150],"present":[151],"complete":[153],"core":[154],"architecture,":[155],"compare":[157],"its":[158],"projected":[159,209],"power,":[160],"performance,":[161],"efficiency":[164,185,203,229],"against":[165],"equivalent":[167],"SRAM":[168],"baseline,":[169],"showing":[170],"3.8":[172],"<inline-formula":[174,192],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[175,193],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[176,194],"<tex-math":[177,195],"notation=\"LaTeX\">$9.6":[178],"\\times":[179,197],"$":[180,198],"</tex-math></inline-formula>":[181,199],"improvement":[182,200],"total":[184],"(in":[186,204],"GOPS/W/mm2)":[187],"2.2":[190],"notation=\"LaTeX\">$5.6":[196],"GOPS/W).":[205],"addition,":[207],"performance":[211],"Bayes2IMC":[213],"surpasses":[214],"most":[215],"memristive":[216],"BNN":[217],"architectures":[218],"reported":[219],"literature,":[222],"up":[224],"20%":[226],"higher":[227],"compared":[230],"state-of-the-art.":[233]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
