{"id":"https://openalex.org/W4416342081","doi":"https://doi.org/10.1109/socc66126.2025.11235419","title":"BayNNgine: Hardware-Enabled Bayesian Neural Network Support for Dependable AI Inference","display_name":"BayNNgine: Hardware-Enabled Bayesian Neural Network Support for Dependable AI Inference","publication_year":2025,"publication_date":"2025-09-29","ids":{"openalex":"https://openalex.org/W4416342081","doi":"https://doi.org/10.1109/socc66126.2025.11235419"},"language":null,"primary_location":{"id":"doi:10.1109/socc66126.2025.11235419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/socc66126.2025.11235419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 38th International System-on-Chip Conference (SOCC)","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/A5021252999","display_name":"Julian Hoefer","orcid":"https://orcid.org/0000-0003-4904-0495"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Julian Hoefer","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074661835","display_name":"Fabian Lesniak","orcid":"https://orcid.org/0000-0001-8302-6086"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Lesniak","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099073593","display_name":"Annina Gutermann","orcid":"https://orcid.org/0009-0001-9917-8081"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Annina Gutermann","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120410258","display_name":"Felix W\u00f6ran","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix W\u00f6ran","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053259767","display_name":"Tanja Harbaum","orcid":"https://orcid.org/0000-0001-7310-567X"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tanja Harbaum","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":null,"display_name":"Juergen Becker","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Juergen Becker","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":3.346,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.93685126,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7795000076293945,"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":0.7795000076293945,"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":0.08470000326633453,"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/T11005","display_name":"Radiation Effects in Electronics","score":0.03189999982714653,"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/redundancy","display_name":"Redundancy (engineering)","score":0.5961999893188477},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5846999883651733},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4862000048160553},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4636000096797943},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4503999948501587},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4072999954223633},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.385699987411499},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.37040001153945923}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7631000280380249},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5961999893188477},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5846999883651733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5019999742507935},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4562999904155731},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4503999948501587},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4072999954223633},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.385699987411499},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29339998960494995},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26669999957084656},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/socc66126.2025.11235419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/socc66126.2025.11235419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 38th International System-on-Chip Conference (SOCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2289252105","https://openalex.org/W2785369415","https://openalex.org/W3007788310","https://openalex.org/W3035963492","https://openalex.org/W3043426275","https://openalex.org/W3135126155","https://openalex.org/W3211621070","https://openalex.org/W4213433078","https://openalex.org/W4226337850","https://openalex.org/W4308886937","https://openalex.org/W4378800858","https://openalex.org/W4379115972","https://openalex.org/W4386764918","https://openalex.org/W4388206277","https://openalex.org/W4399486726","https://openalex.org/W4399772534","https://openalex.org/W4404482014","https://openalex.org/W4404564552"],"related_works":[],"abstract_inverted_index":{"Driven":[0],"by":[1],"the":[2,35,68,119,123,129,132],"advent":[3],"of":[4,38,58,67,87,122,162],"powerful":[5],"AI-based":[6,28],"computer":[7],"vision":[8],"models":[9,17,29],"founded":[10],"on":[11,172],"Deep":[12],"Neural":[13,89],"Networks,":[14,90],"integrating":[15],"these":[16,74],"into":[18],"safety-critical":[19],"systems":[20],"is":[21,139,178],"increasingly":[22],"appealing.":[23],"However,":[24],"unlike":[25],"traditional":[26],"systems,":[27],"face":[30],"novel":[31],"challenges":[32],"in":[33,48,108,118],"achieving":[34],"required":[36],"level":[37],"dependability.":[39],"This":[40],"includes":[41],"that":[42,104],"AI-models":[43],"tend":[44],"to":[45],"be":[46,106],"overconfident":[47],"their":[49],"predictions":[50],"and":[51,82,126,151,165],"do":[52],"not":[53],"inherently":[54],"provide":[55],"a":[56,80],"measure":[57],"failure":[59],"when":[60],"confronted":[61],"with":[62],"out-of":[63],"distribution":[64],"cases,":[65],"incapabilities":[66],"model,":[69],"or":[70],"hardware":[71],"errors.To":[72],"tackle":[73],"challenges,":[75],"new":[76],"safety":[77],"standards":[78],"recommend":[79],"redundancy":[81],"diversity":[83],"approach,":[84],"e.g.,":[85],"approximations":[86],"Bayesian":[88],"which":[91],"significantly":[92],"increases":[93],"compute":[94,124],"demand.":[95],"To":[96],"mitigate":[97],"this":[98],"burden,":[99],"we":[100],"present":[101],"architectural":[102],"extensions":[103],"can":[105],"integrated":[107],"modern":[109],"neural":[110],"processing":[111],"units.":[112],"By":[113],"incorporating":[114],"flexible":[115],"stochastic":[116],"modules":[117],"data":[120,130],"paths":[121],"array":[125],"thereby":[127],"keeping":[128],"local,":[131],"need":[133],"for":[134,181],"costly":[135],"off-chip":[136],"memory":[137],"accesses":[138],"drastically":[140],"reduced.":[141],"We":[142],"demonstrate":[143],"our":[144,153,176],"approach":[145,177],"using":[146],"an":[147,173],"open-source":[148],"accelerator":[149],"architecture":[150],"make":[152],"contributions":[154],"openly":[155],"available":[156],"as":[157],"well1.":[158],"With":[159],"only":[160],"1-2%":[161],"additional":[163],"resources":[164],"no":[166],"latency":[167],"increase":[168],"per":[169],"redundant":[170],"sample":[171],"FPGA":[174],"implementation,":[175],"well":[179],"adapted":[180],"resource-constrained":[182],"embedded":[183],"real-time":[184],"systems.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-17T00:00:00"}