{"id":"https://openalex.org/W4385187213","doi":"https://doi.org/10.1109/iscas46773.2023.10181925","title":"Low Power Hardware Architecture for Sampling-free Bayesian Neural Networks inference","display_name":"Low Power Hardware Architecture for Sampling-free Bayesian Neural Networks inference","publication_year":2023,"publication_date":"2023-05-21","ids":{"openalex":"https://openalex.org/W4385187213","doi":"https://doi.org/10.1109/iscas46773.2023.10181925"},"language":"en","primary_location":{"id":"doi:10.1109/iscas46773.2023.10181925","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iscas46773.2023.10181925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5112965472","display_name":"Antonios-Kyrillos Chatzimichail","orcid":null},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]},{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["GR","SA"],"is_corresponding":false,"raw_author_name":"Antonios-Kyrillos Chatzimichail","raw_affiliation_strings":["King Abdullah University of Science and Technology (KAUST),Innovative Technologies Laboratories (ITL),Thuwal,Saudi Arabia","Department of Electrical and Computer Engineering, University of Thessaly, Volos, Greece","Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Abdullah University of Science and Technology (KAUST),Innovative Technologies Laboratories (ITL),Thuwal,Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Thessaly, Volos, Greece","institution_ids":["https://openalex.org/I145722265"]},{"raw_affiliation_string":"Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041803182","display_name":"Charalampos Antoniadis","orcid":"https://orcid.org/0000-0002-5902-5240"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Charalampos Antoniadis","raw_affiliation_strings":["King Abdullah University of Science and Technology (KAUST),Innovative Technologies Laboratories (ITL),Thuwal,Saudi Arabia","Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Abdullah University of Science and Technology (KAUST),Innovative Technologies Laboratories (ITL),Thuwal,Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]},{"raw_affiliation_string":"Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062849403","display_name":"Nikolaos Bellas","orcid":"https://orcid.org/0000-0002-9522-9136"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos Bellas","raw_affiliation_strings":["University of Thessaly,Department of Electrical and Computer Engineering,Volos,Greece","Department of Electrical and Computer Engineering, University of Thessaly, Volos, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Thessaly,Department of Electrical and Computer Engineering,Volos,Greece","institution_ids":["https://openalex.org/I145722265"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Thessaly, Volos, Greece","institution_ids":["https://openalex.org/I145722265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057380866","display_name":"Yehia Massoud","orcid":"https://orcid.org/0000-0002-6701-0639"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Yehia Massoud","raw_affiliation_strings":["King Abdullah University of Science and Technology (KAUST),Innovative Technologies Laboratories (ITL),Thuwal,Saudi Arabia","Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Abdullah University of Science and Technology (KAUST),Innovative Technologies Laboratories (ITL),Thuwal,Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]},{"raw_affiliation_string":"Innovative Technologies Laboratories (ITL), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07506376,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"29","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9991999864578247,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9957000017166138,"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/polynomial","display_name":"Polynomial","score":0.6167075037956238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6028822660446167},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5243863463401794},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.5172596573829651},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49231159687042236},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.4829823076725006},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46850043535232544},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.465082585811615},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.43101435899734497},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.34802189469337463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28649765253067017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25773078203201294},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10009711980819702}],"concepts":[{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.6167075037956238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028822660446167},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5243863463401794},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.5172596573829651},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49231159687042236},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.4829823076725006},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46850043535232544},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.465082585811615},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.43101435899734497},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.34802189469337463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28649765253067017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25773078203201294},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10009711980819702},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscas46773.2023.10181925","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iscas46773.2023.10181925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.kaust.edu.sa:10754/693199","is_oa":false,"landing_page_url":"http://hdl.handle.net/10754/693199","pdf_url":null,"source":{"id":"https://openalex.org/S4306401596","display_name":"King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71920554","host_organization_name":"King Abdullah University of Science and Technology","host_organization_lineage":["https://openalex.org/I71920554"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2112796928","https://openalex.org/W2335728318","https://openalex.org/W2750384547","https://openalex.org/W2785369415","https://openalex.org/W2943723147","https://openalex.org/W3035963492","https://openalex.org/W3043426275","https://openalex.org/W3100840543","https://openalex.org/W3101788429","https://openalex.org/W3143351795","https://openalex.org/W3211621070","https://openalex.org/W4282053837","https://openalex.org/W4292862526","https://openalex.org/W6703116779","https://openalex.org/W6743688258","https://openalex.org/W6785904751","https://openalex.org/W6792226486","https://openalex.org/W6841870600"],"related_works":["https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W2010643158","https://openalex.org/W3049691116","https://openalex.org/W2106867672","https://openalex.org/W4310268968","https://openalex.org/W3081214562","https://openalex.org/W2753713401","https://openalex.org/W2053745677"],"abstract_inverted_index":{"Standard":[0],"NNs":[1],"should":[2],"not":[3],"be":[4],"employed":[5],"mindlessly":[6],"in":[7,93,153,162],"critical":[8],"applications":[9],"due":[10,138],"to":[11,14,110,139,191,214,221],"their":[12,19,34],"incapability":[13],"express":[15],"the":[16,22,31,43,49,62,73,91,100,140,143,163,188,200,206],"uncertainty":[17,32],"of":[18,33,51,66,77,102,123,142,165,203],"predictions.":[20,35],"On":[21],"other":[23],"hand,":[24],"Bayesian":[25],"Neural":[26,193],"Networks":[27,194],"(BNNs)":[28],"can":[29],"measure":[30],"There":[36],"are":[37,70,116],"two":[38],"methods":[39],"for":[40,130,180],"BNN":[41,80],"inference,":[42],"Monte":[44,86],"Carlo-based":[45],"method,":[46],"which":[47],"requires":[48],"sampling":[50],"weights":[52],"distributions":[53],"and":[54,58,64,186],"multiple":[55],"inference":[56,81,92],"iterations,":[57],"moment":[59,78,124],"propagation,":[60],"where":[61],"mean":[63],"variance":[65],"a":[67,94,148,177],"normal":[68],"distribution":[69,103],"propagated":[71],"through":[72,105],"BNN.":[74],"Hardware":[75,121],"implementations":[76,122],"propagation":[79,101,125],"consume":[82],"less":[83],"power":[84],"than":[85],"Carlo":[87],"because":[88,99],"they":[89],"complete":[90],"single":[95,149],"forward":[96],"pass.":[97],"However,":[98],"moments":[104],"nonlinear":[106],"activation":[107,145,183],"functions":[108,115],"leads":[109],"large":[111],"hardware":[112,189],"designs,":[113],"these":[114],"usually":[117],"approximated":[118],"by":[119,211],"polynomials.":[120],"have":[126],"been":[127],"studied":[128],"solely":[129],"fully-connected":[131],"neural":[132],"networks":[133],"while":[134],"lacking":[135],"optimal":[136],"accuracy":[137,169,217],"approximation":[141,164,179,202],"ReLU":[144,204],"function":[146],"with":[147,170,218],"polynomial":[150,160,178,210],"term.":[151],"Therefore,":[152],"this":[154],"work,":[155],"we":[156],"add":[157],"one":[158],"more":[159],"term":[161],"ReLU,":[166],"providing":[167],"better":[168],"negligible":[171],"additional":[172],"hardware.":[173],"We":[174],"also":[175],"propose":[176],"another":[181],"common":[182],"function,":[184],"tanh,":[185],"extend":[187],"implementation":[190],"Convolutional":[192],"(CNNs).":[195],"Experimental":[196],"results":[197],"demonstrated":[198],"that":[199],"proposed":[201],"outperforms":[205],"previously":[207],"suggested":[208],"single-term":[209],"achieving":[212],"up":[213,220],"5.9%":[215],"higher":[216],"merely":[219],"0.029$W$power":[222],"overhead.":[223]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}