{"id":"https://openalex.org/W7204794634","doi":"https://doi.org/10.48550/arxiv.2608.28245","title":"I-FLOP: Fast Learning of Order and Parents from Interventional Data","display_name":"I-FLOP: Fast Learning of Order and Parents from Interventional Data","publication_year":2026,"publication_date":"2026-08-28","ids":{"openalex":"https://openalex.org/W7204794634","doi":"https://doi.org/10.48550/arxiv.2608.28245"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.28245","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28245","pdf_url":"https://arxiv.org/pdf/2608.28245","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.28245","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148800149","display_name":"Liuting Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Chen, Liuting","raw_affiliation_strings":["Department of Mathematical Sciences University of Copenhagen Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences University of Copenhagen Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123200873","display_name":"Alex Markham","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Markham, Alex","raw_affiliation_strings":["Department of Mathematical Sciences University of Copenhagen Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences University of Copenhagen Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I124055696"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9994999766349792,"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":0.9994999766349792,"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/T10136","display_name":"Statistical Methods and Inference","score":0.00019999999494757503,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.0,"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-discovery","display_name":"causal discovery","score":0.8270000219345093},{"id":"https://openalex.org/keywords/interventional-data","display_name":"interventional data","score":0.9629999995231628},{"id":"https://openalex.org/keywords/directed-acyclic-graphs","display_name":"directed acyclic graphs","score":0.7850000262260437},{"id":"https://openalex.org/keywords/cholesky-decomposition","display_name":"Cholesky decomposition","score":0.7580000162124634},{"id":"https://openalex.org/keywords/score-based-structure-learning","display_name":"score-based structure learning","score":0.6349999904632568}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5594000220298767},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5099999904632568},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46869999170303345},{"id":"https://openalex.org/C117619785","wikidata":"https://www.wikidata.org/wiki/Q6094414","display_name":"Iterative learning control","level":3,"score":0.45739999413490295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45339998602867126},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.43849998712539673},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3294000029563904},{"id":"https://openalex.org/C176248197","wikidata":"https://www.wikidata.org/wiki/Q458526","display_name":"Probably approximately correct learning","level":4,"score":0.3287000060081482},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2777044963","wikidata":"https://www.wikidata.org/wiki/Q5384707","display_name":"Equivalence class (music)","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29100000858306885},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26829999685287476},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.28245","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28245","pdf_url":"https://arxiv.org/pdf/2608.28245","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.28245","doi":"https://doi.org/10.48550/arxiv.2608.28245","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.28245","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.28245","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.28245","pdf_url":"https://arxiv.org/pdf/2608.28245","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322436","display_name":"Novo Nordisk","ror":"https://ror.org/0435rc536"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204794634.pdf","grobid_xml":"https://content.openalex.org/works/W7204794634.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1510240814","https://openalex.org/W1518076737","https://openalex.org/W1668219064","https://openalex.org/W2083803549","https://openalex.org/W2095690451","https://openalex.org/W2111061246","https://openalex.org/W2138997118","https://openalex.org/W2144731007","https://openalex.org/W2164551395","https://openalex.org/W2307253082","https://openalex.org/W2462800345","https://openalex.org/W2790376986","https://openalex.org/W4310500228","https://openalex.org/W4406401114","https://openalex.org/W7160856380"],"related_works":["https://openalex.org/W2980460915","https://openalex.org/W2979821415","https://openalex.org/W2788968049","https://openalex.org/W2103659055","https://openalex.org/W4283792726","https://openalex.org/W1532777422","https://openalex.org/W2053775054","https://openalex.org/W2620708460","https://openalex.org/W3097530345","https://openalex.org/W4388093831"],"abstract_inverted_index":{"We":[0,54,76],"extend":[1],"the":[2,27,42,58,66,73],"FLOP":[3],"(fast":[4],"learning":[5,83],"of":[6,31,97],"order":[7],"and":[8,33,87,100],"parents)":[9],"algorithm":[10],"recently":[11],"proposed":[12],"by":[13],"Wien\u00f6bst":[14],"et":[15],"al.":[16],"(2026)":[17],"from":[18],"observational":[19],"to":[20,38,79],"interventional":[21,28,68,89],"data.":[22],"In":[23],"particular,":[24],"we":[25],"use":[26],"BIC":[29],"score":[30,45],"Hauser":[32],"B\u00fchlmann":[34],"(2012),":[35],"adapting":[36],"it":[37,92],"be":[39],"used":[40],"with":[41],"iterative":[43],"Cholesky-based":[44],"updates":[46],"that":[47],"are":[48],"partly":[49],"responsible":[50],"for":[51],"FLOP's":[52],"speed.":[53],"show":[55],"that,":[56],"in":[57,65,95],"sample":[59],"limit,":[60],"I-FLOP":[61,78],"recovers":[62],"a":[63],"DAG":[64],"same":[67],"Markov":[69],"equivalence":[70],"class":[71],"as":[72],"data-generating":[74],"DAG.":[75],"compare":[77],"existing":[80],"causal":[81],"structure":[82],"algorithms":[84],"on":[85],"real":[86],"simulated":[88],"data,":[90],"where":[91],"performs":[93],"favorably":[94],"terms":[96],"both":[98],"performance":[99],"run":[101],"time.":[102]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-01T00:00:00"}
