{"id":"https://openalex.org/W4297679051","doi":"https://doi.org/10.1145/3549737.3549775","title":"An evaluation framework for comparing causal inference models","display_name":"An evaluation framework for comparing causal inference models","publication_year":2022,"publication_date":"2022-09-07","ids":{"openalex":"https://openalex.org/W4297679051","doi":"https://doi.org/10.1145/3549737.3549775"},"language":"en","primary_location":{"id":"doi:10.1145/3549737.3549775","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549737.3549775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th Hellenic Conference on Artificial Intelligence","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/A5015815927","display_name":"Niki Kiriakidou","orcid":"https://orcid.org/0000-0003-1729-4124"},"institutions":[{"id":"https://openalex.org/I32762134","display_name":"Harokopio University of Athens","ror":"https://ror.org/02k5gp281","country_code":"GR","type":"education","lineage":["https://openalex.org/I32762134"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Niki Kiriakidou","raw_affiliation_strings":["Informatics and Telematics, Harokopio University of Athens, Greece"],"affiliations":[{"raw_affiliation_string":"Informatics and Telematics, Harokopio University of Athens, Greece","institution_ids":["https://openalex.org/I32762134"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004953619","display_name":"Christos Diou","orcid":"https://orcid.org/0000-0002-2461-1928"},"institutions":[{"id":"https://openalex.org/I32762134","display_name":"Harokopio University of Athens","ror":"https://ror.org/02k5gp281","country_code":"GR","type":"education","lineage":["https://openalex.org/I32762134"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Christos Diou","raw_affiliation_strings":["Informatics and Telematics, Harokopio University of Athens, Greece"],"affiliations":[{"raw_affiliation_string":"Informatics and Telematics, Harokopio University of Athens, Greece","institution_ids":["https://openalex.org/I32762134"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015815927"],"corresponding_institution_ids":["https://openalex.org/I32762134"],"apc_list":null,"apc_paid":null,"fwci":0.9724,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76669353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.80640709400177},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6983602046966553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.673341691493988},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.624843418598175},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5926785469055176},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5774641633033752},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.5381096601486206},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.53168123960495},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.5199435949325562},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.5165764093399048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5019192695617676},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45092129707336426},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.43735596537590027},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42420631647109985},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35698413848876953},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3459942638874054},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23593690991401672},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16673994064331055},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08219122886657715}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.80640709400177},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6983602046966553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.673341691493988},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.624843418598175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5926785469055176},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5774641633033752},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.5381096601486206},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.53168123960495},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.5199435949325562},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.5165764093399048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5019192695617676},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45092129707336426},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.43735596537590027},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42420631647109985},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35698413848876953},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3459942638874054},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23593690991401672},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16673994064331055},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08219122886657715},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3549737.3549775","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3549737.3549775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th Hellenic Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2016944307","https://openalex.org/W2064903582","https://openalex.org/W2096166399","https://openalex.org/W2126292488","https://openalex.org/W2169284845","https://openalex.org/W2208550830","https://openalex.org/W2579895585","https://openalex.org/W2624816748","https://openalex.org/W2914114370","https://openalex.org/W2949241286","https://openalex.org/W2955553835","https://openalex.org/W3006323900","https://openalex.org/W4302364527","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W3215034539","https://openalex.org/W4313422683","https://openalex.org/W4282978140","https://openalex.org/W2148385623","https://openalex.org/W2894915327","https://openalex.org/W2161504683","https://openalex.org/W2951813053","https://openalex.org/W2542556882","https://openalex.org/W4386240783","https://openalex.org/W2888243788"],"abstract_inverted_index":{"Estimation":[0,68],"of":[1,8,42,52,55,64,69,82,94,115,118,122],"causal":[2,37,83,147],"effects":[3,21],"is":[4,112],"the":[5,20,49,53,56,65,80,91,113,116,127,135,139],"core":[6],"objective":[7],"many":[9],"scientific":[10],"disciplines.":[11],"However,":[12],"it":[13],"remains":[14],"a":[15,119],"challenging":[16],"task,":[17],"especially":[18],"when":[19],"are":[22],"estimated":[23],"from":[24],"observational":[25],"data.":[26],"Recently,":[27],"several":[28,145],"promising":[29],"machine":[30],"learning":[31],"models":[32,44,85],"have":[33],"been":[34,46],"proposed":[35,140],"for":[36],"effect":[38,148],"estimation.":[39],"The":[40,106],"evaluation":[41,81,141],"these":[43],"has":[45],"based":[47],"on":[48,126],"mean":[50],"values":[51],"error":[54],"Average":[57],"Treatment":[58],"Effect":[59,71],"(ATE)":[60],"as":[61,63,98,100],"well":[62,99],"Precision":[66],"in":[67,131],"Heterogeneous":[70],"(PEHE).":[72],"In":[73],"this":[74,110],"paper,":[75],"we":[76],"propose":[77],"to":[78,143],"complement":[79],"inference":[84],"using":[86],"concrete":[87],"statistical":[88,104],"evidence,":[89],"including":[90],"performance":[92],"profiles":[93],"Dolan":[95],"and":[96,102],"Mor\u00e9,":[97],"non-parametric":[101],"post-hoc":[103],"tests.":[105],"main":[107],"motivation":[108],"behind":[109],"approach":[111],"elimination":[114],"influence":[117],"small":[120],"number":[121],"instances":[123],"or":[124],"simulation":[125],"benchmarking":[128],"process,":[129],"which":[130],"some":[132],"cases":[133],"dominate":[134],"results.":[136],"We":[137],"use":[138],"methodology":[142],"compare":[144],"state-of-the-art":[146],"estimation":[149],"models.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
