{"id":"https://openalex.org/W4385568008","doi":"https://doi.org/10.1145/3580305.3599809","title":"DNet: Distributional Network for Distributional Individualized Treatment Effects","display_name":"DNet: Distributional Network for Distributional Individualized Treatment Effects","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568008","doi":"https://doi.org/10.1145/3580305.3599809"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599809","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599809","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchonline.lse.ac.uk/id/eprint/122895/1/Distributional_Network_for_Distributional_Individualized.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007832673","display_name":"Guojun Wu","orcid":"https://orcid.org/0000-0002-2524-7996"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Guojun Wu","raw_affiliation_strings":["Bytedance, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Bytedance, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014078198","display_name":"Ge Song","orcid":"https://orcid.org/0009-0007-9045-1161"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge Song","raw_affiliation_strings":["Bytedance, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Bytedance, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052009101","display_name":"X.F. Lv","orcid":"https://orcid.org/0009-0005-2680-5645"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoxiang Lv","raw_affiliation_strings":["Bytedance, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Bytedance, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101330846","display_name":"Shikai Luo","orcid":"https://orcid.org/0009-0005-3567-2194"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shikai Luo","raw_affiliation_strings":["Bytedance, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Bytedance, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025970743","display_name":"Chengchun Shi","orcid":"https://orcid.org/0000-0001-7773-2099"},"institutions":[{"id":"https://openalex.org/I909854389","display_name":"London School of Economics and Political Science","ror":"https://ror.org/0090zs177","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I909854389"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chengchun Shi","raw_affiliation_strings":["London School of Economics and Political Science, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"London School of Economics and Political Science, London, United Kingdom","institution_ids":["https://openalex.org/I909854389"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077961759","display_name":"Hongtu Zhu","orcid":"https://orcid.org/0000-0002-6781-2690"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongtu Zhu","raw_affiliation_strings":["University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill, Chapel Hill, NC, USA","institution_ids":["https://openalex.org/I114027177"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5007832673"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9951,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77492212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5215","last_page":"5224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9955999851226807,"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":0.9955999851226807,"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/T13283","display_name":"Mental Health Research Topics","score":0.9387000203132629,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9192000031471252,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.787303626537323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.701793909072876},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5269794464111328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.507218599319458},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.4455220103263855},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.42812061309814453},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4222121834754944},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11672121286392212},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1149669885635376}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.787303626537323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.701793909072876},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5269794464111328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.507218599319458},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.4455220103263855},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.42812061309814453},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4222121834754944},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11672121286392212},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1149669885635376},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3580305.3599809","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599809","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:researchonline.lse.ac.uk:122895","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-7773-2099>","pdf_url":"https://researchonline.lse.ac.uk/id/eprint/122895/1/Distributional_Network_for_Distributional_Individualized.pdf","source":{"id":"https://openalex.org/S4306400050","display_name":"London School of Economics and Political Science Theses Online (London School of Economics and Political Science)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I909854389","host_organization_name":"London School of Economics and Political Science","host_organization_lineage":["https://openalex.org/I909854389"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:RePEc:ehl:lserod:122895","is_oa":false,"landing_page_url":"http://eprints.lse.ac.uk/122895/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"preprint"}],"best_oa_location":{"id":"pmh:oai:researchonline.lse.ac.uk:122895","is_oa":true,"landing_page_url":"https://orcid.org/0000-0001-7773-2099>","pdf_url":"https://researchonline.lse.ac.uk/id/eprint/122895/1/Distributional_Network_for_Distributional_Individualized.pdf","source":{"id":"https://openalex.org/S4306400050","display_name":"London School of Economics and Political Science Theses Online (London School of Economics and Political Science)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I909854389","host_organization_name":"London School of Economics and Political Science","host_organization_lineage":["https://openalex.org/I909854389"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385568008.pdf","grobid_xml":"https://content.openalex.org/works/W4385568008.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1516659296","https://openalex.org/W1573647811","https://openalex.org/W1590049149","https://openalex.org/W1967525463","https://openalex.org/W1970739592","https://openalex.org/W1978108654","https://openalex.org/W2064903582","https://openalex.org/W2085048097","https://openalex.org/W2133596638","https://openalex.org/W2154065358","https://openalex.org/W2164952673","https://openalex.org/W2165231911","https://openalex.org/W2208550830","https://openalex.org/W2258149283","https://openalex.org/W2624816748","https://openalex.org/W2708031219","https://openalex.org/W2946130033","https://openalex.org/W2948807347","https://openalex.org/W2951225967","https://openalex.org/W2962727190","https://openalex.org/W2963052087","https://openalex.org/W2970278855","https://openalex.org/W3001202326","https://openalex.org/W3005828485","https://openalex.org/W3070774468","https://openalex.org/W3123436326","https://openalex.org/W3124999902","https://openalex.org/W3148604462","https://openalex.org/W3149414568","https://openalex.org/W4237922950","https://openalex.org/W4294249992","https://openalex.org/W6634147026","https://openalex.org/W6774475447"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2378211422","https://openalex.org/W2347460059","https://openalex.org/W2111726165","https://openalex.org/W4321353415","https://openalex.org/W2745001401"],"abstract_inverted_index":{"There":[0],"is":[1],"a":[2,27,94],"growing":[3],"interest":[4],"in":[5,70,79,93],"developing":[6],"methods":[7,49,78],"to":[8,32],"estimate":[9],"individualized":[10],"treatment":[11,56],"effects":[12],"(ITEs)":[13],"for":[14,43],"various":[15],"real-world":[16,85],"applications,":[17],"such":[18],"as":[19],"e-commerce":[20],"and":[21,58,75,84],"public":[22],"health.":[23],"This":[24],"paper":[25],"presents":[26],"novel":[28],"architecture,":[29],"called":[30],"DNet,":[31],"infer":[33],"distributional":[34],"ITEs.":[35],"DNet":[36,87],"can":[37],"learn":[38],"the":[39,53,60],"entire":[40],"outcome":[41],"distribution":[42],"each":[44],"treatment,":[45],"whereas":[46],"most":[47],"existing":[48],"primarily":[50],"focus":[51],"on":[52,82],"conditional":[54,61],"average":[55],"effect":[57],"ignore":[59],"variance":[62],"around":[63],"its":[64],"expectation.":[65],"Additionally,":[66],"our":[67],"method":[68],"excels":[69],"settings":[71],"with":[72,99],"heavy-tailed":[73],"outcomes":[74],"outperforms":[76],"state-of-the-art":[77],"extensive":[80],"experiments":[81],"benchmark":[83],"datasets.":[86],"has":[88],"also":[89],"been":[90],"successfully":[91],"deployed":[92],"widely":[95],"used":[96],"mobile":[97],"app":[98],"millions":[100],"of":[101],"daily":[102],"active":[103],"users.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
