{"id":"https://openalex.org/W7135231435","doi":"https://doi.org/10.48550/arxiv.2603.11565","title":"CAETC: Causal Autoencoding and Treatment Conditioning for Counterfactual Estimation over Time","display_name":"CAETC: Causal Autoencoding and Treatment Conditioning for Counterfactual Estimation over Time","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135231435","doi":"https://doi.org/10.48550/arxiv.2603.11565"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11565","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11565","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.11565","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125908678","display_name":"Nghia Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Nghia D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129088822","display_name":"Pablo Robles-Granda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robles-Granda, Pablo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065423139","display_name":"Lav R. Varshney","orcid":"https://orcid.org/0000-0003-2798-5308"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Varshney, Lav R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.44749999046325684,"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":0.44749999046325684,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.2159000039100647,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.1006999984383583,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9501000046730042},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.6184999942779541},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.6121000051498413},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5841000080108643},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5444999933242798},{"id":"https://openalex.org/keywords/confounding","display_name":"Confounding","score":0.366100013256073},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.361299991607666},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.3481000065803528},{"id":"https://openalex.org/keywords/invertible-matrix","display_name":"Invertible matrix","score":0.3456000089645386}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9501000046730042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6355000138282776},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.6184999942779541},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.6121000051498413},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5841000080108643},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5444999933242798},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5078999996185303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44040000438690186},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4343000054359436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4196999967098236},{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.361299991607666},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C96442724","wikidata":"https://www.wikidata.org/wiki/Q242188","display_name":"Invertible matrix","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C45262634","wikidata":"https://www.wikidata.org/wiki/Q5159291","display_name":"Conditioning","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3012999892234802},{"id":"https://openalex.org/C162144332","wikidata":"https://www.wikidata.org/wiki/Q1665305","display_name":"Instrumental variable","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C176743888","wikidata":"https://www.wikidata.org/wiki/Q862797","display_name":"Observational methods in psychology","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11565","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11565","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.11565","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11565","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Counterfactual":[0],"estimation":[1,125],"over":[2,126],"time":[3],"is":[4,69,81],"important":[5],"in":[6,17,25,123],"various":[7],"applications,":[8],"such":[9,95],"as":[10,71,96],"personalized":[11],"medicine.":[12],"However,":[13],"time-dependent":[14],"confounding":[15],"bias":[16],"observational":[18],"data":[19,115],"still":[20],"poses":[21],"a":[22,39,58,73],"significant":[23,121],"challenge":[24],"achieving":[26],"accurate":[27],"and":[28,35,61,88,113],"efficient":[29],"estimation.":[30],"We":[31,106],"introduce":[32],"causal":[33],"autoencoding":[34,54],"treatment":[36],"conditioning":[37,75],"(CAETC),":[38],"novel":[40],"method":[41,51],"for":[42],"this":[43],"problem.":[44],"Built":[45],"on":[46,76,110],"adversarial":[47],"representation":[48],"learning,":[49],"our":[50],"leverages":[52],"an":[53],"architecture":[55],"to":[56,92,116],"learn":[57],"partially":[59],"invertible":[60],"treatment-invariant":[62],"representation,":[63],"where":[64],"the":[65,77,84],"outcome":[66],"prediction":[67],"task":[68],"cast":[70],"applying":[72],"treatment-specific":[74],"representation.":[78],"Our":[79],"design":[80],"independent":[82],"of":[83],"underlying":[85],"sequence":[86],"model":[87],"can":[89],"be":[90],"applied":[91],"existing":[93,127],"architectures":[94],"long":[97],"short-term":[98],"memories":[99],"(LSTMs)":[100],"or":[101],"temporal":[102],"convolution":[103],"networks":[104],"(TCNs).":[105],"conduct":[107],"extensive":[108],"experiments":[109],"synthetic,":[111],"semi-synthetic,":[112],"real-world":[114],"demonstrate":[117],"that":[118],"CAETC":[119],"yields":[120],"improvement":[122],"counterfactual":[124],"methods.":[128]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-14T00:00:00"}