{"id":"https://openalex.org/W4395065535","doi":"https://doi.org/10.48550/arxiv.2404.14073","title":"Towards Robust Trajectory Representations: Isolating Environmental\n Confounders with Causal Learning","display_name":"Towards Robust Trajectory Representations: Isolating Environmental\n Confounders with Causal Learning","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W4395065535","doi":"https://doi.org/10.48550/arxiv.2404.14073"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2404.14073","pdf_url":"https://arxiv.org/pdf/2404.14073","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2404.14073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101341259","display_name":"Kang Luo","orcid":"https://orcid.org/0009-0003-5866-0175"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Kang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084537731","display_name":"Yuanshao Zhu","orcid":"https://orcid.org/0000-0002-5657-181X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yuanshao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100761914","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0002-1780-3294"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366705","display_name":"Kun Wang","orcid":"https://orcid.org/0000-0003-0602-169X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Kun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040516967","display_name":"Zhengyang Zhou","orcid":"https://orcid.org/0000-0003-4728-7347"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Zhengyang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006117974","display_name":"Sijie Ruan","orcid":"https://orcid.org/0000-0002-4520-7174"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruan, Sijie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018828723","display_name":"Yuxuan Liang","orcid":"https://orcid.org/0000-0003-2817-7337"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yuxuan","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":83},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9938,"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":0.9938,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9207,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9063,"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/causal-model","display_name":"Causal model","score":0.49862123}],"concepts":[{"id":"https://openalex.org/C77350462","wikidata":"https://www.wikidata.org/wiki/Q1125472","display_name":"Confounding","level":2,"score":0.72075593},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.62843055},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.49862123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45793796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40461797},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.38426954},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3611982},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3541486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21362829},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16719425},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06415033},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2404.14073","pdf_url":"https://arxiv.org/pdf/2404.14073","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2404.14073","pdf_url":"https://arxiv.org/pdf/2404.14073","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W830718730","https://openalex.org/W4246786946","https://openalex.org/W4236720793","https://openalex.org/W2994176440","https://openalex.org/W2793477322","https://openalex.org/W2510575233","https://openalex.org/W2495367848","https://openalex.org/W2481749367","https://openalex.org/W2122231514","https://openalex.org/W1992228662"],"abstract_inverted_index":{"Trajectory":[0,70],"modeling":[1,71],"refers":[2],"to":[3,29,51,88],"characterizing":[4],"human":[5],"movement":[6],"behavior,":[7],"serving":[8],"as":[9,84],"a":[10,46,59,69],"pivotal":[11],"step":[12],"in":[13,110],"understanding":[14],"mobility":[15],"patterns.":[16],"Nevertheless,":[17],"existing":[18],"studies":[19],"typically":[20],"ignore":[21],"the":[22,30,53,64,80,90],"confounding":[23],"effects":[24],"of":[25,32],"geospatial":[26,94],"context,":[27],"leading":[28],"acquisition":[31],"spurious":[33,91],"correlations":[34,92],"and":[35,96,118],"limited":[36],"generalization":[37,117],"capabilities.":[38],"To":[39],"bridge":[40],"this":[41],"gap,":[42],"we":[43,66],"initially":[44],"formulate":[45],"Structural":[47],"Causal":[48,76],"Model":[49],"(SCM)":[50],"decipher":[52],"trajectory":[54,111],"representation":[55],"learning":[56],"process":[57],"from":[58],"causal":[60],"perspective.":[61],"Building":[62],"upon":[63],"SCM,":[65],"further":[67],"present":[68],"framework":[72],"(TrajCL)":[73],"based":[74],"on":[75,100],"Learning,":[77],"which":[78],"leverages":[79],"backdoor":[81],"adjustment":[82],"theory":[83],"an":[85],"intervention":[86],"tool":[87],"eliminate":[89],"between":[93],"context":[95],"trajectories.":[97],"Extensive":[98],"experiments":[99],"two":[101],"real-world":[102],"datasets":[103],"verify":[104],"that":[105],"TrajCL":[106],"markedly":[107],"enhances":[108],"performance":[109],"classification":[112],"tasks":[113],"while":[114],"showcasing":[115],"superior":[116],"interpretability.":[119]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4395065535","counts_by_year":[],"updated_date":"2025-01-19T05:20:34.684278","created_date":"2024-04-24"}