{"id":"https://openalex.org/W3198635030","doi":"https://doi.org/10.1007/s41060-021-00282-0","title":"Repetitive causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders","display_name":"Repetitive causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders","publication_year":2021,"publication_date":"2021-09-07","ids":{"openalex":"https://openalex.org/W3198635030","doi":"https://doi.org/10.1007/s41060-021-00282-0","mag":"3198635030"},"language":"en","primary_location":{"id":"doi:10.1007/s41060-021-00282-0","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s41060-021-00282-0","pdf_url":null,"source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-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/A5090276104","display_name":"Takashi Maeda","orcid":"https://orcid.org/0000-0003-2419-9280"},"institutions":[{"id":"https://openalex.org/I4210110652","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takashi Nicholas Maeda","raw_affiliation_strings":["RIKEN, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2419-9280","affiliations":[{"raw_affiliation_string":"RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210110652"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077846534","display_name":"Shohei Shimizu","orcid":"https://orcid.org/0000-0002-1931-0733"},"institutions":[{"id":"https://openalex.org/I171494771","display_name":"Shiga University","ror":"https://ror.org/01vvhy971","country_code":"JP","type":"education","lineage":["https://openalex.org/I171494771"]},{"id":"https://openalex.org/I4210110652","display_name":"RIKEN","ror":"https://ror.org/01sjwvz98","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shohei Shimizu","raw_affiliation_strings":["RIKEN, Tokyo, Japan","Shiga University, Shiga, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210110652"]},{"raw_affiliation_string":"Shiga University, Shiga, Japan","institution_ids":["https://openalex.org/I171494771"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5090276104"],"corresponding_institution_ids":["https://openalex.org/I4210110652"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":null,"fwci":0.8396,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79002894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"13","issue":"2","first_page":"77","last_page":"89"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9995999932289124,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9995999932289124,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9801999926567078,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T12805","display_name":"Cognitive Science and Mapping","score":0.9610000252723694,"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/confounding","display_name":"Confounding","score":0.8996075391769409},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.7474285364151001},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.5651710033416748},{"id":"https://openalex.org/keywords/causal-structure","display_name":"Causal structure","score":0.5353273749351501},{"id":"https://openalex.org/keywords/structural-equation-modeling","display_name":"Structural equation modeling","score":0.45683497190475464},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.34585273265838623},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3361971974372864},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3213889002799988},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31919100880622864}],"concepts":[{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.8996075391769409},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.7474285364151001},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.5651710033416748},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.5353273749351501},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.45683497190475464},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34585273265838623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3361971974372864},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3213889002799988},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31919100880622864},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s41060-021-00282-0","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s41060-021-00282-0","pdf_url":null,"source":{"id":"https://openalex.org/S4210195017","display_name":"International Journal of Data Science and Analytics","issn_l":"2364-415X","issn":["2364-415X","2364-4168"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319972","host_organization_name":"Springer International Publishing","host_organization_lineage":["https://openalex.org/P4310319972","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer International Publishing","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Science and Analytics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6255199523","display_name":null,"funder_award_id":"ONRG NICOP N62909-17-1-2034","funder_id":"https://openalex.org/F4320338298","funder_display_name":"Office of Naval Research Global"},{"id":"https://openalex.org/G6310765311","display_name":null,"funder_award_id":"20K19872","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6574449418","display_name":null,"funder_award_id":"16K00045","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6726399410","display_name":null,"funder_award_id":"20K11708","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338298","display_name":"Office of Naval Research Global","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W203744573","https://openalex.org/W1565072465","https://openalex.org/W1975062332","https://openalex.org/W2008312103","https://openalex.org/W2011680222","https://openalex.org/W2020925091","https://openalex.org/W2028581488","https://openalex.org/W2051434435","https://openalex.org/W2093947494","https://openalex.org/W2112552549","https://openalex.org/W2132507555","https://openalex.org/W2132547334","https://openalex.org/W2151226328","https://openalex.org/W2163687466","https://openalex.org/W2165582599","https://openalex.org/W2168745915","https://openalex.org/W2171408260","https://openalex.org/W2519023215","https://openalex.org/W2597289420","https://openalex.org/W2604511230","https://openalex.org/W2796901885","https://openalex.org/W2990138404","https://openalex.org/W3037128376","https://openalex.org/W3103539622","https://openalex.org/W3133236490","https://openalex.org/W3198635030","https://openalex.org/W4229977739","https://openalex.org/W4285719527","https://openalex.org/W4299515571"],"related_works":["https://openalex.org/W2013493105","https://openalex.org/W4391170574","https://openalex.org/W2530578176","https://openalex.org/W4254968820","https://openalex.org/W2138020080","https://openalex.org/W2313268639","https://openalex.org/W2734236000","https://openalex.org/W4232115672","https://openalex.org/W1752864923","https://openalex.org/W4372273223"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-11T08:15:01.531666","created_date":"2025-10-10T00:00:00"}