{"id":"https://openalex.org/W2768854788","doi":"https://doi.org/10.1109/codit.2017.8102623","title":"Reconstruction of causal graphs for multivariate processes in the presence of missing data","display_name":"Reconstruction of causal graphs for multivariate processes in the presence of missing data","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2768854788","doi":"https://doi.org/10.1109/codit.2017.8102623","mag":"2768854788"},"language":"en","primary_location":{"id":"doi:10.1109/codit.2017.8102623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit.2017.8102623","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-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/A5038165895","display_name":"Piyush Agarwal","orcid":"https://orcid.org/0000-0002-2187-6883"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Piyush Agarwal","raw_affiliation_strings":["Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064793183","display_name":"Arun K. Tangirala","orcid":"https://orcid.org/0000-0002-7921-5340"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun K. Tangirala","raw_affiliation_strings":["Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5038165895"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":0.1282,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48659256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"16","issue":null,"first_page":"0389","last_page":"0394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11434","display_name":"Electrochemical Analysis and Applications","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1603","display_name":"Electrochemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9851999878883362,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7223175764083862},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6447999477386475},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6353034973144531},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.633179247379303},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.6148597598075867},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.5826647281646729},{"id":"https://openalex.org/keywords/causal-structure","display_name":"Causal structure","score":0.563801109790802},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5126675367355347},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4931723475456238},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.482086718082428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47224849462509155},{"id":"https://openalex.org/keywords/partial-correlation","display_name":"Partial correlation","score":0.44203686714172363},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.44044578075408936},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4189659655094147},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2627217769622803},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.22175580263137817},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.19600945711135864},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13901033997535706}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7223175764083862},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6447999477386475},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6353034973144531},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.633179247379303},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.6148597598075867},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.5826647281646729},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.563801109790802},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5126675367355347},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4931723475456238},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.482086718082428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47224849462509155},{"id":"https://openalex.org/C64708745","wikidata":"https://www.wikidata.org/wiki/Q2998010","display_name":"Partial correlation","level":3,"score":0.44203686714172363},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.44044578075408936},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4189659655094147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2627217769622803},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.22175580263137817},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.19600945711135864},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13901033997535706},{"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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/codit.2017.8102623","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit.2017.8102623","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 4th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W106406567","https://openalex.org/W1919415331","https://openalex.org/W1964058989","https://openalex.org/W1974618482","https://openalex.org/W2002294478","https://openalex.org/W2004416535","https://openalex.org/W2015418199","https://openalex.org/W2016847569","https://openalex.org/W2031668066","https://openalex.org/W2043771676","https://openalex.org/W2069371232","https://openalex.org/W2075926617","https://openalex.org/W2108660034","https://openalex.org/W2136562407","https://openalex.org/W2143428876","https://openalex.org/W2158849324","https://openalex.org/W2167853664","https://openalex.org/W2177793333","https://openalex.org/W2178225550","https://openalex.org/W2179494973","https://openalex.org/W2296616510","https://openalex.org/W2397362117","https://openalex.org/W2511968724","https://openalex.org/W2947626232","https://openalex.org/W2962731902","https://openalex.org/W4250955649","https://openalex.org/W4285719527","https://openalex.org/W6685701956"],"related_works":["https://openalex.org/W2950035905","https://openalex.org/W2072483141","https://openalex.org/W2018580387","https://openalex.org/W3098259173","https://openalex.org/W4312269093","https://openalex.org/W2161504683","https://openalex.org/W3170261037","https://openalex.org/W2753729722","https://openalex.org/W3123305972","https://openalex.org/W3135588948"],"abstract_inverted_index":{"Learning":[0],"temporal":[1],"causal":[2,15,34,77,120,153,169],"relationships":[3],"between":[4,36],"time":[5,100],"series":[6],"is":[7,30,134],"an":[8],"important":[9],"tool":[10],"for":[11,137],"the":[12,33,37,41,76,83,89,94,107,119,157,160,166],"identification":[13],"of":[14,85,109,159,168],"network":[16,28],"structures":[17],"in":[18,27,73],"linear":[19,152],"dynamic":[20,154],"systems":[21,155],"from":[22,44,122],"measurements.":[23],"The":[24,132],"main":[25],"objective":[26],"reconstruction":[29,167],"to":[31,70,104,106,117,165],"identify":[32],"interactions":[35,78],"variables":[38],"and":[39,62,102],"determine":[40],"connectivity":[42],"strengths":[43],"time-series":[45],"data.":[46],"Among":[47],"several":[48],"recently":[49],"introduced":[50],"data-driven":[51],"causality":[52],"measures,":[53],"partial":[54,59],"directed":[55,58],"coherence":[56],"(PDC),":[57],"correlation":[60],"(DPC)":[61],"direct":[63],"power":[64],"transfer":[65],"(DPT)":[66],"have":[67,143],"been":[68],"shown":[69],"be":[71],"effective":[72],"both":[74],"identifying":[75],"as":[79,81],"well":[80],"quantifying":[82],"strength":[84],"connectivity.":[86],"However,":[87],"all":[88,99],"existing":[90],"approaches":[91],"assume":[92],"that":[93,142],"observations":[95,126],"are":[96],"available":[97],"at":[98],"instants":[101],"fail":[103],"cater":[105],"case":[108],"missing":[110,125],"observations.":[111],"This":[112],"paper":[113],"presents":[114],"a":[115],"method":[116,133,162],"reconstruct":[118],"graph":[121],"data":[123],"with":[124,163],"using":[127],"sparse":[128],"optimization":[129],"(SPOPT)":[130],"techniques.":[131],"particularly":[135],"devised":[136],"jointly":[138],"stationary":[139],"multivariate":[140],"processes":[141],"vector":[144],"autoregressive":[145],"(VAR)":[146],"structure":[147],"representations.":[148],"Demonstrations":[149],"on":[150],"different":[151],"illustrate":[156],"efficacy":[158],"proposed":[161],"respect":[164],"networks.":[170]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}