{"id":"https://openalex.org/W4224282912","doi":"https://doi.org/10.1145/3485447.3512030","title":"EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting","display_name":"EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224282912","doi":"https://doi.org/10.1145/3485447.3512030"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512030","doi":"https://doi.org/10.1145/3485447.3512030","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512030","pdf_url":null,"source":{"id":"https://openalex.org/S7407088480","display_name":"International World Wide Web Conference (WWW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2204.08771","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032510266","display_name":"Sheo Yon Jhin","orcid":"https://orcid.org/0000-0001-5930-0735","observed_orcids":["https://orcid.org/0000-0001-5930-0735"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sheo Yon Jhin","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111896688","display_name":"Jaehoon Lee","orcid":"https://orcid.org/0000-0001-9777-5918","observed_orcids":["https://orcid.org/0000-0001-9777-5918"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehoon Lee","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059043259","display_name":"Minju Jo","orcid":"https://orcid.org/0000-0002-2684-9788","observed_orcids":["https://orcid.org/0000-0002-2684-9788"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minju Jo","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029742759","display_name":"Seungji Kook","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungji Kook","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059294187","display_name":"Jinsung Jeon","orcid":"https://orcid.org/0000-0002-9693-2739","observed_orcids":["https://orcid.org/0000-0002-9693-2739"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinsung Jeon","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018858017","display_name":"Jihyeon Hyeong","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jihyeon Hyeong","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100612966","display_name":"Jayoung Kim","orcid":"https://orcid.org/0000-0003-2946-8478","observed_orcids":["https://orcid.org/0000-0003-2946-8478","https://orcid.org/0000-0002-0294-9565"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jayoung Kim","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067253588","display_name":"Noseong Park","orcid":"https://orcid.org/0000-0002-1268-840X","observed_orcids":["https://orcid.org/0000-0002-1268-840X"]},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Noseong Park","raw_affiliation_strings":["Yonsei University, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":3.4373,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.94459196,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3102","last_page":"3112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9057999849319458,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9057999849319458,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10320","display_name":"Neural Networks and Applications","score":0.04569999873638153,"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/T11416","display_name":"Numerical Solvers for Ordinary Differential Equations","score":0.008899999782443047,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"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/neural-controlled-differential-equations","display_name":"neural controlled differential equations","score":0.9959999918937683},{"id":"https://openalex.org/keywords/time-series-classification","display_name":"time series classification","score":0.8090000152587891},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.9950000047683716},{"id":"https://openalex.org/keywords/interpolation","display_name":"interpolation","score":0.8169999718666077},{"id":"https://openalex.org/keywords/extrapolation","display_name":"extrapolation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/encoder-decoder-architecture","display_name":"encoder-decoder architecture","score":0.7480000257492065},{"id":"https://openalex.org/keywords/irregular-time-series","display_name":"irregular time series","score":0.7749999761581421}],"concepts":[{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.8546816110610962},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.7758115530014038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.688654899597168},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5593972206115723},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.542801022529602},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5364950299263},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.47961151599884033},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4650880694389343},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.451968252658844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4055027663707733},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20826146006584167},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07894250750541687},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3485447.3512030","doi":"https://doi.org/10.1145/3485447.3512030","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512030","pdf_url":null,"source":{"id":"https://openalex.org/S7407088480","display_name":"International World Wide Web Conference (WWW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2204.08771","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.08771","pdf_url":"https://arxiv.org/pdf/2204.08771","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2204.08771","doi":"https://doi.org/10.48550/arxiv.2204.08771","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2204.08771","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:2204.08771","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.08771","pdf_url":"https://arxiv.org/pdf/2204.08771","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":"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/F4320321314","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224282912.pdf","grobid_xml":"https://content.openalex.org/works/W4224282912.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W100459338","https://openalex.org/W1591801644","https://openalex.org/W1924770834","https://openalex.org/W1977542511","https://openalex.org/W2012244785","https://openalex.org/W2064675550","https://openalex.org/W2070803964","https://openalex.org/W2077791698","https://openalex.org/W2144144709","https://openalex.org/W2160535745","https://openalex.org/W2169125069","https://openalex.org/W2503637115","https://openalex.org/W2773049109","https://openalex.org/W2781585732","https://openalex.org/W2797583228","https://openalex.org/W2898647012","https://openalex.org/W2899534962","https://openalex.org/W2945959973","https://openalex.org/W2948760323","https://openalex.org/W3000476444","https://openalex.org/W3007066689","https://openalex.org/W3022643593","https://openalex.org/W3174804935","https://openalex.org/W4226061867"],"related_works":["https://openalex.org/W4382460977","https://openalex.org/W4226061867","https://openalex.org/W7167541477","https://openalex.org/W3174804935","https://openalex.org/W4378768643","https://openalex.org/W4392007959","https://openalex.org/W4416017977","https://openalex.org/W3170815717","https://openalex.org/W7127405257","https://openalex.org/W4416552983"],"abstract_inverted_index":{"Deep":[0],"learning":[1,23,166],"inspired":[2],"by":[3,70,186],"differential":[4,32],"equations":[5,33],"is":[6,35],"a":[7,38,77,81],"recent":[8],"research":[9],"trend":[10],"and":[11,130,159,175,180],"has":[12],"marked":[13],"the":[14,17,115,126,133,137,142,157,160],"state":[15],"of":[16,118,136,145],"art":[18],"performance":[19],"for":[20,163],"many":[21,41],"machine":[22,165],"tasks.":[24,167],"Among":[25],"them,":[26],"time-series":[27,83,93],"modeling":[28],"with":[29,171],"neural":[30,52,122],"controlled":[31],"(NCDEs)":[34],"considered":[36],"as":[37],"breakthrough.":[39],"In":[40,64,168],"cases,":[42],"NCDE-based":[43],"models":[44],"not":[45],"only":[46],"provide":[47],"better":[48],"accuracy":[49],"than":[50],"recurrent":[51],"networks":[53],"(RNNs)":[54],"but":[55],"also":[56],"make":[57],"it":[58],"possible":[59],"to":[60,90,95,101,114],"process":[61,117],"irregular":[62],"time-series.":[63],"this":[65],"work,":[66],"we":[67,99],"enhance":[68],"NCDEs":[69,85,182],"redesigning":[71],"their":[72],"core":[73],"part,":[74],"i.e.,":[75,120,139],"generating":[76],"continuous":[78,96,106],"path":[79,107],"from":[80],"discrete":[82,92],"input.":[84],"typically":[86],"use":[87,155],"interpolation":[88,116,124],"algorithms":[89],"convert":[91],"samples":[94],"paths.":[97],"However,":[98],"propose":[100],"i)":[102],"generate":[103],"another":[104],"latent":[105],"using":[108],"an":[109],"encoder-decoder":[110],"architecture,":[111],"which":[112],"corresponds":[113],"NCDEs,":[119],"our":[121,151,169,178],"network-based":[123],"vs.":[125],"existing":[127,184],"explicit":[128],"interpolation,":[129],"ii)":[131],"exploit":[132],"generative":[134],"characteristic":[135],"decoder,":[138],"extrapolation":[140,179],"beyond":[141],"time":[143],"domain":[144],"original":[146],"data":[147],"if":[148],"needed.":[149],"Therefore,":[150],"NCDE":[152],"design":[153],"can":[154],"both":[156],"interpolated":[158],"extrapolated":[161],"information":[162],"downstream":[164],"experiments":[170],"5":[172],"real-world":[173],"datasets":[174],"12":[176],"baselines,":[177],"interpolation-based":[181],"outperform":[183],"baselines":[185],"non-trivial":[187],"margins.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-04-26T00:00:00"}