{"id":"https://openalex.org/W7128162811","doi":"https://doi.org/10.1145/3796240","title":"Modeling Dynamic Interference for Treatment Effect Estimation from Dynamic Graphs","display_name":"Modeling Dynamic Interference for Treatment Effect Estimation from Dynamic Graphs","publication_year":2026,"publication_date":"2026-02-06","ids":{"openalex":"https://openalex.org/W7128162811","doi":"https://doi.org/10.1145/3796240"},"language":"en","primary_location":{"id":"doi:10.1145/3796240","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3796240","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5125279137","display_name":"Xiaofeng Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaofeng Lin","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4147-3037","affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Han Bao","orcid":"https://orcid.org/0000-0002-4473-2604"},"institutions":[{"id":"https://openalex.org/I4210134673","display_name":"The Institute of Statistical Mathematics","ror":"https://ror.org/03jcejr58","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I4210134673","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Han Bao","raw_affiliation_strings":["The Institute of Statistical Mathematics, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4473-2604","affiliations":[{"raw_affiliation_string":"The Institute of Statistical Mathematics, Tokyo, Japan","institution_ids":["https://openalex.org/I4210134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088800219","display_name":"Koh Takeuchi","orcid":"https://orcid.org/0000-0002-3245-888X"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koh Takeuchi","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3245-888X","affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125260812","display_name":"Yan Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Cui","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0009-0003-6066-8117","affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, Pennsylvania, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125277995","display_name":"Hisashi Kashima","orcid":null},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hisashi Kashima","raw_affiliation_strings":["Graduate School of Informatics, Kyoto University, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-2770-0184","affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Kyoto University, Kyoto, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18353735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"3","first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.27149999141693115,"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":0.27149999141693115,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.22139999270439148,"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/T12488","display_name":"Mental Health via Writing","score":0.06719999760389328,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.678600013256073},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.6000000238418579},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5985999703407288},{"id":"https://openalex.org/keywords/dynamic-network-analysis","display_name":"Dynamic network analysis","score":0.42559999227523804},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4016000032424927},{"id":"https://openalex.org/keywords/prior-information","display_name":"Prior information","score":0.33719998598098755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491999864578247},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.678600013256073},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.6000000238418579},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5985999703407288},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43560001254081726},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.42559999227523804},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40689998865127563},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36160001158714294},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C2987370644","wikidata":"https://www.wikidata.org/wiki/Q7836903","display_name":"Treatment effect","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.310699999332428}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3796240","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3796240","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7075013518333435,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1638081485","https://openalex.org/W1995906082","https://openalex.org/W1998029376","https://openalex.org/W2012797835","https://openalex.org/W2036443429","https://openalex.org/W2064675550","https://openalex.org/W2162941511","https://openalex.org/W2314734263","https://openalex.org/W2735728227","https://openalex.org/W2996910665","https://openalex.org/W2998496395","https://openalex.org/W3037367072","https://openalex.org/W3078674662","https://openalex.org/W3115643957","https://openalex.org/W3171375092","https://openalex.org/W3208674193","https://openalex.org/W4214806201","https://openalex.org/W4290943920","https://openalex.org/W4293064632","https://openalex.org/W4298042940","https://openalex.org/W4306317407","https://openalex.org/W4387847699","https://openalex.org/W4389098833","https://openalex.org/W4392157641","https://openalex.org/W4394600732","https://openalex.org/W4394964969","https://openalex.org/W4401246912"],"related_works":[],"abstract_inverted_index":{"Estimating":[0],"treatment":[1,18,39],"effects":[2],"can":[3,50,113],"assist":[4],"decision-making":[5],"in":[6,96],"various":[7],"areas,":[8],"such":[9],"as":[10,37,58,70,138],"commerce":[11],"and":[12,129,161,182],"medicine.":[13],"One":[14],"application":[15],"of":[16,26,33,47,55,111,159,214,253],"the":[17,24,30,45,90,109,156,212,215,219,223,251],"effect":[19,25,40],"estimation":[20,82,242],"is":[21,67],"to":[22,69,76,100,137,153,209,221],"predict":[23],"an":[27,48,151,169,183],"advertisement":[28],"on":[29,229],"purchase":[31],"result":[32],"a":[34,84,205],"customer,":[35],"known":[36],"individual":[38,49],"(ITE).":[41],"In":[42,106,142,226],"online":[43],"websites,":[44],"outcome":[46],"be":[51,114],"affected":[52],"by":[53,119,126,149,177,191],"treatments":[54,120,130],"other":[56],"individuals,":[57],"people":[59],"often":[60],"propagate":[61],"information":[62,128,158,197],"with":[63,116,232],"their":[64,162],"friends.":[65],"This":[66],"referred":[68],"interference.":[71],"Prior":[72],"studies":[73],"have":[74],"attempted":[75],"model":[77,146,220],"interference":[78,140,148,175,189,255],"for":[79,121,131,240],"accurate":[80],"ITE":[81,241],"under":[83],"static":[85],"network":[86,91],"among":[87,104],"individuals.":[88,105],"However,":[89],"usually":[92],"changes":[93,200],"over":[94,201],"time":[95],"real-world":[97],"applications":[98],"due":[99],"complex":[101],"social":[102],"activities":[103],"this":[107,143],"case,":[108],"outcomes":[110],"individuals":[112,160,178,192,199],"interfered":[115],"not":[117],"only":[118],"current":[122],"neighbors":[123],"but":[124],"also":[125],"past":[127,132,157],"neighbors,":[133],"which":[134,173,187,217,249],"we":[135,145,203],"refer":[136],"dynamic":[139,147,233,247,254],".":[141],"work,":[144],"developing":[150],"architecture":[152],"aggregate":[154],"both":[155],"neighbors.":[163],"Specifically,":[164],"our":[165,227,235],"proposed":[166],"method":[167,236],"contains":[168],"attention-based":[170,184],"historical":[171],"aggregation,":[172,186],"models":[174],"received":[176,190],"from":[179],"previous":[180],"timestamps,":[181],"neighbor":[185],"captures":[188],"within":[193],"every":[194],"timestamp.":[195],"Since":[196],"about":[198],"time,":[202],"propose":[204],"parameter":[206],"evolution":[207],"trick":[208],"adaptively":[210],"update":[211],"parameters":[213],"model,":[216],"enables":[218],"capture":[222,246],"dynamics":[224],"effectively.":[225],"experiments":[228],"multiple":[230],"datasets":[231],"interference,":[234,248],"outperforms":[237],"existing":[238],"methods":[239],"because":[243],"they":[244],"cannot":[245],"corroborates":[250],"importance":[252],"modeling.":[256]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-07T00:00:00"}