{"id":"https://openalex.org/W3016648615","doi":"https://doi.org/10.1109/icaiic48513.2020.9065256","title":"Bayesian Inference and Learning for Neural Networks and Deep Learning","display_name":"Bayesian Inference and Learning for Neural Networks and Deep Learning","publication_year":2020,"publication_date":"2020-02-01","ids":{"openalex":"https://openalex.org/W3016648615","doi":"https://doi.org/10.1109/icaiic48513.2020.9065256","mag":"3016648615"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic48513.2020.9065256","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5016293435","display_name":"Sunghae Jun","orcid":"https://orcid.org/0000-0003-1961-0055"},"institutions":[{"id":"https://openalex.org/I22586776","display_name":"Cheongju University","ror":"https://ror.org/02tx4na66","country_code":"KR","type":"education","lineage":["https://openalex.org/I22586776"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sunghae Jun","raw_affiliation_strings":["Department of Big Data and Statistics, Cheongju University, Chungbuk, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Big Data and Statistics, Cheongju University, Chungbuk, Korea","institution_ids":["https://openalex.org/I22586776"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016293435"],"corresponding_institution_ids":["https://openalex.org/I22586776"],"apc_list":null,"apc_paid":null,"fwci":0.345,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56115074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"569","last_page":"571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9810000061988831,"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/T10320","display_name":"Neural Networks and Applications","score":0.9789000153541565,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7923650741577148},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6796483397483826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6429195404052734},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.6257579326629639},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.612586259841919},{"id":"https://openalex.org/keywords/bayesian-statistics","display_name":"Bayesian statistics","score":0.5884512662887573},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5378737449645996},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5374278426170349},{"id":"https://openalex.org/keywords/variable-order-bayesian-network","display_name":"Variable-order Bayesian network","score":0.5206084251403809},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.50887131690979},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.48001614212989807},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.44554319977760315}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7923650741577148},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6796483397483826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6429195404052734},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.6257579326629639},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.612586259841919},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.5884512662887573},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5378737449645996},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5374278426170349},{"id":"https://openalex.org/C71983512","wikidata":"https://www.wikidata.org/wiki/Q7915687","display_name":"Variable-order Bayesian network","level":4,"score":0.5206084251403809},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.50887131690979},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.48001614212989807},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.44554319977760315}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic48513.2020.9065256","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic48513.2020.9065256","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W368469426","https://openalex.org/W1567512734","https://openalex.org/W2466916924","https://openalex.org/W2501634593","https://openalex.org/W3020204246","https://openalex.org/W4240484282","https://openalex.org/W4248681815"],"related_works":["https://openalex.org/W2383034311","https://openalex.org/W2592745513","https://openalex.org/W2169561303","https://openalex.org/W2570816834","https://openalex.org/W2006239736","https://openalex.org/W2604705913","https://openalex.org/W4328114192","https://openalex.org/W2352852554","https://openalex.org/W1484024982","https://openalex.org/W4308145032"],"abstract_inverted_index":{"Bayesian":[0,22,60,75,88],"statistics":[1,23,61],"has":[2],"a":[3,84],"lot":[4],"of":[5,21,37],"influence":[6],"on":[7,26,87],"neural":[8,93],"networks":[9,94],"and":[10,19,29,40,57,77,82,90,95],"deep":[11,96],"learning":[12,20,48,54,65,78,91],"for":[13,66,80,92],"artificial":[14],"intelligence":[15],"(AI).":[16],"The":[17,31],"inference":[18,76,89],"is":[24,33,43],"based":[25,86],"prior,":[27],"likelihood":[28],"posterior.":[30],"prior":[32,56],"the":[34,41,44,73],"current":[35],"belief":[36,46],"data":[38,64],"field":[39],"posterior":[42,58],"updated":[45],"after":[47],"from":[49],"observed":[50],"data.":[51],"By":[52],"repeated":[53],"using":[55],"distributions,":[59],"provides":[62],"advanced":[63],"AI.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"compare":[72],"previous":[74],"methods":[79],"AI":[81],"propose":[83],"model":[85],"learning.":[97]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}