{"id":"https://openalex.org/W2904638191","doi":"https://doi.org/10.1007/s10115-018-1286-7","title":"Telling cause from effect by local and global regression","display_name":"Telling cause from effect by local and global regression","publication_year":2018,"publication_date":"2018-12-07","ids":{"openalex":"https://openalex.org/W2904638191","doi":"https://doi.org/10.1007/s10115-018-1286-7","mag":"2904638191"},"language":"en","primary_location":{"id":"doi:10.1007/s10115-018-1286-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-018-1286-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-018-1286-7.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10115-018-1286-7.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053408235","display_name":"Alexander Marx","orcid":"https://orcid.org/0000-0002-1575-824X"},"institutions":[{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]},{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alexander Marx","raw_affiliation_strings":["Max Planck Institute for Informatics and Saarland University, Saarland Informatics Campus, Saarbr\u00fccken, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Informatics and Saarland University, Saarland Informatics Campus, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712","https://openalex.org/I91712215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043872748","display_name":"Jilles Vreeken","orcid":"https://orcid.org/0000-0002-2310-2806"},"institutions":[{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]},{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jilles Vreeken","raw_affiliation_strings":["Max Planck Institute for Informatics and Saarland University, Saarland Informatics Campus, Saarbr\u00fccken, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Informatics and Saarland University, Saarland Informatics Campus, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712","https://openalex.org/I91712215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053408235"],"corresponding_institution_ids":["https://openalex.org/I4210109712","https://openalex.org/I91712215"],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":{"value":2890,"currency":"USD","value_usd":2890},"fwci":1.3281,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.83374736,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"60","issue":"3","first_page":"1277","last_page":"1305"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12002","display_name":"Computability, Logic, AI Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9962000250816345,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9901999831199646,"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/mathematics","display_name":"Mathematics","score":0.6054919958114624},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5539693236351013},{"id":"https://openalex.org/keywords/conditional-independence","display_name":"Conditional independence","score":0.5266813039779663},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.515480101108551},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.5109049677848816},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46868637204170227},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42754703760147095},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.427384614944458},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.42607975006103516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3635616898536682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3045530915260315},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2629970908164978},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2339031994342804},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1976190209388733},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.18714049458503723}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6054919958114624},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5539693236351013},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.5266813039779663},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.515480101108551},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.5109049677848816},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46868637204170227},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42754703760147095},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.427384614944458},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.42607975006103516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3635616898536682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3045530915260315},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2629970908164978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2339031994342804},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1976190209388733},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.18714049458503723}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s10115-018-1286-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-018-1286-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-018-1286-7.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/24612594","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Telling_cause_from_effect_by_local_and_global_regression/24612594","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:pure.mpg.de:item_3012091","is_oa":true,"landing_page_url":"http://hdl.handle.net/21.11116/0000-0002-9EAD-A","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Knowledge and Information Systems","raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.60882/cispa.24612594.v1","is_oa":true,"landing_page_url":"https://doi.org/10.60882/cispa.24612594.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050916","display_name":"CISPA Helmholtz Center","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"JournalArticle"}],"best_oa_location":{"id":"doi:10.1007/s10115-018-1286-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10115-018-1286-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10115-018-1286-7.pdf","source":{"id":"https://openalex.org/S81770430","display_name":"Knowledge and Information Systems","issn_l":"0219-1377","issn":["0219-1377","0219-3116"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge and Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"},{"id":"https://openalex.org/F4320317967","display_name":"International Max Planck Research School for Environmental, Cellular and Molecular Microbiology","ror":null},{"id":"https://openalex.org/F4320322434","display_name":"Max-Planck-Gesellschaft","ror":"https://ror.org/01hhn8329"},{"id":"https://openalex.org/F4320327553","display_name":"International Max Planck Research School for Advanced Methods in Process and Systems Engineering","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904638191.pdf","grobid_xml":"https://content.openalex.org/works/W2904638191.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W235810693","https://openalex.org/W811835876","https://openalex.org/W1497574396","https://openalex.org/W1524326598","https://openalex.org/W1568555062","https://openalex.org/W1638203394","https://openalex.org/W1731081199","https://openalex.org/W1850984366","https://openalex.org/W1991445071","https://openalex.org/W2005097301","https://openalex.org/W2054658115","https://openalex.org/W2068774186","https://openalex.org/W2083689856","https://openalex.org/W2101460669","https://openalex.org/W2106596127","https://openalex.org/W2110065044","https://openalex.org/W2110381504","https://openalex.org/W2123329644","https://openalex.org/W2132547334","https://openalex.org/W2143891888","https://openalex.org/W2146531590","https://openalex.org/W2147881172","https://openalex.org/W2151226328","https://openalex.org/W2164001983","https://openalex.org/W2164524421","https://openalex.org/W2165582599","https://openalex.org/W2165700458","https://openalex.org/W2284008599","https://openalex.org/W2290557121","https://openalex.org/W2564078846","https://openalex.org/W2573830947","https://openalex.org/W2618188015","https://openalex.org/W2745281314","https://openalex.org/W2758592735","https://openalex.org/W2769454077","https://openalex.org/W2798428896","https://openalex.org/W2909010126","https://openalex.org/W3003623942","https://openalex.org/W3094506902","https://openalex.org/W3099283977","https://openalex.org/W3106124465","https://openalex.org/W3123545922","https://openalex.org/W3124338716","https://openalex.org/W4252684946","https://openalex.org/W4302423442"],"related_works":["https://openalex.org/W1828158523","https://openalex.org/W2047547195","https://openalex.org/W204175656","https://openalex.org/W1993992974","https://openalex.org/W1512294453","https://openalex.org/W2911841387","https://openalex.org/W2738234280","https://openalex.org/W2550734047","https://openalex.org/W4294753120","https://openalex.org/W3112629828"],"abstract_inverted_index":{"We":[0],"consider":[1],"the":[2,6,27,36,49,68,81,85,90,95,120,127,139,161,179,202,217,226,240,243],"problem":[3],"of":[4,78,94,110,129,134,184,242],"inferring":[5],"causal":[7,87,149],"direction":[8,51],"between":[9],"two":[10,211],"univariate":[11],"numeric":[12],"random":[13],"variables":[14],"X":[15,29,40,105,123,135],"and":[16,42,125,166,192,229],"Y":[17,31,38,111,130],"from":[18],"observational":[19],"data.":[20],"This":[21,72,98],"case":[22],"is":[23,32,45,89,106,207],"especially":[24],"challenging":[25],"as":[26,131],"graph":[28,37],"causes":[30,39],"Markov":[33,70],"equivalent":[34],"to":[35,47,117,157,170,177],",":[41,124,136],"hence":[43],"it":[44],"impossible":[46],"determine":[48,171,197],"correct":[50],"using":[52,181],"conditional":[53],"independence":[54],"tests.":[55],"To":[56,153,196],"tackle":[57],"this":[58,145,155],"problem,":[59],"we":[60,101,113,147,159,175,209,224,237],"follow":[61],"an":[62,199],"information":[63],"theoretic":[64],"approach":[65],"based":[66,215],"on":[67,216],"algorithmic":[69],"condition.":[71],"postulate":[73],"states":[74],"that":[75,100,104,187,232],"in":[76,144,204],"terms":[77],"Kolmogorov":[79],"complexity":[80],"factorization":[82],"given":[83],"by":[84,151,245],"true":[86],"model":[88,189],"most":[91],"succinct":[92],"description":[93],"joint":[96],"distribution.":[97],"means":[99],"can":[102,188],"infer":[103],"a":[107,132,168,182,246],"likely":[108],"cause":[109],"when":[112],"need":[114,176],"fewer":[115],"bits":[116,174],"first":[118],"transmit":[119,178],"data":[121,128,180],"over":[122],"then":[126],"function":[133],"than":[137],"for":[138],"inverse":[140],"direction.":[141],"That":[142],"is,":[143],"paper":[146],"perform":[148],"inference":[150],"compression.":[152],"put":[154],"notion":[156],"practice,":[158],"employ":[160],"Minimum":[162],"Description":[163],"Length":[164],"principle,":[165],"propose":[167,210],"score":[169],"how":[172],"many":[173],"class":[183],"regression":[185],"functions":[186],"both":[190],"local":[191],"global":[193],"functional":[194],"relations.":[195],"whether":[198],"inference,":[200],"i.e.":[201],"difference":[203],"compressed":[205],"sizes,":[206],"significant,":[208],"analytical":[212],"significance":[213],"tests":[214],"no-hypercompression":[218],"inequality.":[219],"Last,":[220],"but":[221],"not":[222],"least,":[223],"introduce":[225],"linear-time":[227],"Slope":[228],"Sloper":[230],"algorithms":[231],"through":[233],"thorough":[234],"empirical":[235],"evaluation":[236],"show":[238],"outperform":[239],"state":[241],"art":[244],"wide":[247],"margin.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}