{"id":"https://openalex.org/W4404564552","doi":"https://doi.org/10.1109/dft63277.2024.10753546","title":"BayWatch: Leveraging Bayesian Neural Networks for Hardware Fault Tolerance and Monitoring","display_name":"BayWatch: Leveraging Bayesian Neural Networks for Hardware Fault Tolerance and Monitoring","publication_year":2024,"publication_date":"2024-10-08","ids":{"openalex":"https://openalex.org/W4404564552","doi":"https://doi.org/10.1109/dft63277.2024.10753546"},"language":"en","primary_location":{"id":"doi:10.1109/dft63277.2024.10753546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dft63277.2024.10753546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)","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/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":true,"raw_author_name":"Julian Hoefer","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"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/A5102891258","display_name":"Matthias Stammler","orcid":"https://orcid.org/0009-0006-8843-1076"},"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":"Matthias Stammler","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"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/A5040618617","display_name":"Fabian Kre\u00df","orcid":"https://orcid.org/0000-0002-1700-5778"},"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 Kre\u00df","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"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/A5091579417","display_name":"Tim Hotfilter","orcid":"https://orcid.org/0000-0001-9748-3149"},"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":"Tim Hotfilter","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany"],"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"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024739574","display_name":"J\u00fcrgen Becker","orcid":"https://orcid.org/0000-0002-5082-5487"},"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"],"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":6,"corresponding_author_ids":["https://openalex.org/A5021252999"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":1.3978,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82483928,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9553999900817871,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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":0.78013014793396},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5458089709281921},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.5410875082015991},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5375162959098816},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.49403125047683716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39410144090652466},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.392780065536499},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3731474280357361},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3457905948162079},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3288148045539856},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.20437324047088623}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.78013014793396},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5458089709281921},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.5410875082015991},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5375162959098816},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.49403125047683716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39410144090652466},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.392780065536499},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3731474280357361},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3457905948162079},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3288148045539856},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.20437324047088623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dft63277.2024.10753546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dft63277.2024.10753546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G1466237240","display_name":null,"funder_award_id":"16ME0096","funder_id":"https://openalex.org/F4320321114","funder_display_name":"Bundesministerium f\u00fcr Bildung und Forschung"}],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2767260595","https://openalex.org/W2948194985","https://openalex.org/W2995393114","https://openalex.org/W3034230713","https://openalex.org/W3043426275","https://openalex.org/W3117257709","https://openalex.org/W4284673614","https://openalex.org/W4319835976","https://openalex.org/W4378800858","https://openalex.org/W4379115972","https://openalex.org/W4386336889","https://openalex.org/W4386901271","https://openalex.org/W4388206277","https://openalex.org/W6752760542"],"related_works":["https://openalex.org/W2972991241","https://openalex.org/W2165143308","https://openalex.org/W2319821665","https://openalex.org/W2381390841","https://openalex.org/W1967767358","https://openalex.org/W2139348078","https://openalex.org/W2955463503","https://openalex.org/W4367181073","https://openalex.org/W4360591956","https://openalex.org/W2385565048"],"abstract_inverted_index":{"As":[0],"Deep":[1],"Neural":[2,65],"Networks":[3,66],"are":[4],"increasingly":[5],"being":[6],"utilized":[7],"in":[8,24,157,161],"safety-critical":[9],"domains,":[10],"assessing":[11],"the":[12,15,26,113],"uncertainty":[13,89,115,141],"of":[14,112],"models":[16,78],"during":[17],"inference":[18,71],"will":[19],"be":[20],"a":[21,56,109,154],"crucial":[22],"component":[23],"enhancing":[25],"system's":[27],"dependability.":[28],"Furthermore,":[29,137],"dependable":[30],"AI":[31],"systems":[32],"need":[33],"to":[34,45,75,127,133],"provide":[35],"measures":[36],"against":[37],"random":[38],"hardware":[39],"faults,":[40],"since":[41,153],"they":[42],"can":[43,124,143],"lead":[44],"false":[46],"and":[47,72,87],"possibly":[48],"hazardous":[49],"predictions.":[50],"To":[51],"address":[52],"this,":[53],"we":[54,138],"present":[55],"novel":[57],"fault":[58,85,101,117,130],"analysis":[59,96],"methodology,":[60],"specifically":[61],"tailored":[62],"for":[63,149],"Bayesian":[64,80],"(BayNNs).":[67],"We":[68,91],"utilize":[69],"variational":[70],"dropout":[73],"techniques":[74],"transform":[76],"deterministic":[77,135],"into":[79],"models,":[81],"thereby":[82],"increasing":[83],"their":[84,134],"tolerance":[86,131],"enabling":[88],"monitoring.":[90],"conduct":[92],"an":[93,146,158],"extensive":[94],"comparative":[95],"involving":[97],"over":[98],"12":[99],"million":[100],"injection":[102],"experiments":[103],"across":[104],"two":[105],"distinct":[106],"networks,":[107],"providing":[108],"comprehensive":[110],"understanding":[111],"network's":[114],"under":[116],"conditions.":[118],"Our":[119],"results":[120,156],"demonstrate":[121],"that":[122,140],"BayNNs":[123],"exhibit":[125],"up":[126],"2x":[128],"greater":[129],"compared":[132],"counterparts.":[136],"show":[139],"monitoring":[142],"serve":[144],"as":[145],"effective":[147],"tool":[148],"revealing":[150],"fault-induced":[151],"errors,":[152],"bit-flip":[155],"error":[159],"only":[160],"predictions":[162],"with":[163],"high":[164],"uncertainty.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
