{"id":"https://openalex.org/W7155489596","doi":"https://doi.org/10.1109/icsc67292.2026.00023","title":"Efficient Uncertainty Propagation in Continuous Bayesian Networks Using GUM and Monte Carlo Methods","display_name":"Efficient Uncertainty Propagation in Continuous Bayesian Networks Using GUM and Monte Carlo Methods","publication_year":2026,"publication_date":"2026-02-02","ids":{"openalex":"https://openalex.org/W7155489596","doi":"https://doi.org/10.1109/icsc67292.2026.00023"},"language":null,"primary_location":{"id":"doi:10.1109/icsc67292.2026.00023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsc67292.2026.00023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Semantic Computing (ICSC)","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/A5041939592","display_name":"Lu\u00edsa Hoffmann","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":"Luisa Hoffmann","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Institute of Industrial Information Technology (IIIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Institute of Industrial Information Technology (IIIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065874009","display_name":"Michael Heizmann","orcid":"https://orcid.org/0000-0001-9339-2055"},"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":"Michael Heizmann","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Institute of Industrial Information Technology (IIIT),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Institute of Industrial Information Technology (IIIT),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134483843","display_name":"Ali Darijani","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":"Ali Darijani","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Institute for Anthropomatics and Robotics (IAR),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Institute for Anthropomatics and Robotics (IAR),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073930300","display_name":"J\u00fcrgen Beyerer","orcid":"https://orcid.org/0000-0003-3556-7181"},"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":"J\u00fcrgen Beyerer","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT),Institute for Anthropomatics and Robotics (IAR),Karlsruhe,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Institute for Anthropomatics and Robotics (IAR),Karlsruhe,Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.64237591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"119","last_page":"123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.219200000166893,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.219200000166893,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.16869999468326569,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.14100000262260437,"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/monte-carlo-method","display_name":"Monte Carlo method","score":0.5885999798774719},{"id":"https://openalex.org/keywords/propagation-of-uncertainty","display_name":"Propagation of uncertainty","score":0.5382000207901001},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4832000136375427},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4296000003814697},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.387800008058548},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.350600004196167},{"id":"https://openalex.org/keywords/uncertainty-analysis","display_name":"Uncertainty analysis","score":0.3483000099658966}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5885999798774719},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5166000127792358},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4832000136375427},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4296000003814697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42010000348091125},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3707999885082245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37049999833106995},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C177803969","wikidata":"https://www.wikidata.org/wiki/Q29205","display_name":"Uncertainty analysis","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.31709998846054077},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.30079999566078186},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C176147448","wikidata":"https://www.wikidata.org/wiki/Q1889114","display_name":"Sensitivity analysis","level":3,"score":0.29600000381469727},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28529998660087585},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.27140000462532043},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.263700008392334}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsc67292.2026.00023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsc67292.2026.00023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Semantic Computing (ICSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W621546036","https://openalex.org/W1534500549","https://openalex.org/W1965612527","https://openalex.org/W2560589809","https://openalex.org/W2754518627","https://openalex.org/W2883939481","https://openalex.org/W2991211569","https://openalex.org/W3128604560","https://openalex.org/W4320800818","https://openalex.org/W4392959680"],"related_works":[],"abstract_inverted_index":{"In":[0,46],"large":[1],"and":[2,14,56,75,94,128,155,173,177,187,218,237],"complex":[3],"systems":[4],"such":[5,224],"as":[6,106,201,225],"the":[7,47,96,99,138,163,214,226],"Circular":[8,227],"Factory,":[9],"vast":[10],"amounts":[11],"of":[12,49,101,162],"heterogeneous":[13,53],"uncertain":[15],"data":[16,55],"are":[17,150],"generated.":[18],"Classical":[19],"Bayesian":[20,85],"Networks":[21,86],"(BNs)":[22],"provide":[23],"a":[24,81,107,132,202,232],"principled":[25],"framework":[26,82,211],"for":[27,83,110,126,159,205,216],"reasoning":[28,67,119,221,236],"under":[29],"uncertainty,":[30],"but":[31],"their":[32,41,175],"reliance":[33],"on":[34],"discrete":[35,89],"Conditional":[36],"Probability":[37],"Tables":[38],"(CPTs)":[39],"limits":[40],"applicability":[42],"in":[43,103,131,192,222],"continuous":[44,73,84,121,242],"domains.":[45],"context":[48],"semantic":[50,238,254],"computing,":[51],"where":[52],"sensor":[54],"knowledge":[57],"graph":[58],"information":[59,244],"must":[60],"be":[61,246],"integrated,":[62],"this":[63],"limitation":[64],"prevents":[65],"probabilistic":[66,118,235],"from":[68],"being":[69],"consistently":[70],"applied":[71],"to":[72,98,152,245],"quantities":[74],"measurement-based":[76],"information.":[77],"This":[78,210],"paper":[79],"introduces":[80],"that":[87,182],"replaces":[88],"CPTs":[90],"with":[91,145],"functional":[92],"dependencies":[93],"integrates":[95],"Guide":[97],"Expression":[100],"Uncertainty":[102],"Measurement":[104],"(GUM)":[105],"standardized":[108],"approach":[109],"analytical":[111,139],"uncertainty":[112,130,190,220,243],"propagation.":[113],"The":[114,179],"proposed":[115],"method":[116],"enables":[117],"over":[120],"variables":[122],"while":[123,196],"explicitly":[124],"accounting":[125],"measurement":[127],"parameter":[129],"mathematically":[133],"transparent":[134],"way.":[135],"To":[136],"complement":[137],"formulation,":[140],"Monte":[141,197],"Carlo":[142,198],"(MC)":[143],"simulations":[144],"Gaussian":[146],"Mixture":[147],"Models":[148],"(GMMs)":[149],"employed":[151],"handle":[153],"non-linear":[154,208],"non-Gaussian":[156],"cases,":[157],"allowing":[158],"numerical":[160],"validation":[161],"GUM":[164],"approximation.":[165],"We":[166],"present":[167],"illustrative":[168],"examples":[169],"comparing":[170],"both":[171],"approaches":[172],"discuss":[174],"agreement":[176],"limitations.":[178],"results":[180],"demonstrate":[181],"GUM-based":[183],"inference":[184],"provides":[185,231],"accurate":[186],"computationally":[188],"efficient":[189],"estimates":[191],"locally":[193],"linear":[194],"regions,":[195],"methods":[199],"serve":[200],"reliable":[203],"benchmark":[204],"more":[206],"complex,":[207],"dependencies.":[209],"thus":[212,251],"lays":[213],"foundation":[215],"robust":[217],"interpretable":[219],"environments":[223],"Factory.":[228],"Furthermore,":[229],"it":[230],"bridge":[233],"between":[234],"representations":[239],"by":[240],"enabling":[241],"embedded":[247],"within":[248],"knowledge-based":[249],"systems,":[250],"advancing":[252],"uncertainty-aware":[253],"computing.":[255]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-25T00:00:00"}