{"id":"https://openalex.org/W4220727308","doi":"https://doi.org/10.1109/tpami.2022.3161649","title":"Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling","display_name":"Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling","publication_year":2022,"publication_date":"2022-03-23","ids":{"openalex":"https://openalex.org/W4220727308","doi":"https://doi.org/10.1109/tpami.2022.3161649","pmid":"https://pubmed.ncbi.nlm.nih.gov/35320087"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3161649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3161649","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xuhui Fan","orcid":"https://orcid.org/0000-0002-7558-7200"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Xuhui Fan","raw_affiliation_strings":["UNSW uDash, School of Mathematics &amp; Statistics, University of New South Wales Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-7558-7200","affiliations":[{"raw_affiliation_string":"UNSW uDash, School of Mathematics &amp; Statistics, University of New South Wales Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yaqiong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yaqiong Li","raw_affiliation_strings":["Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ling Chen","orcid":"https://orcid.org/0000-0002-6468-5729"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ling Chen","raw_affiliation_strings":["Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-6468-5729","affiliations":[{"raw_affiliation_string":"Australian Artificial Intelligence Institute, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bin Li","orcid":"https://orcid.org/0000-0002-9633-0033"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9633-0033","affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":null,"display_name":"Scott A. Sisson","orcid":"https://orcid.org/0000-0001-8943-067X"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Scott A. Sisson","raw_affiliation_strings":["UNSW uDash, School of Mathematics &amp; Statistics, University of New South Wales Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0001-8943-067X","affiliations":[{"raw_affiliation_string":"UNSW uDash, School of Mathematics &amp; Statistics, University of New South Wales Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.3558,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44495619,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"45","issue":"2","first_page":"1848","last_page":"1861"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.9235000014305115,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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/T11830","display_name":"Point processes and geometric inequalities","score":0.9235000014305115,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.028200000524520874,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.01080000028014183,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.5698999762535095},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5102999806404114},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5001999735832214},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.44040000438690186},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4284999966621399},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4147999882698059},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.4074999988079071},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.39149999618530273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.652899980545044},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.5698999762535095},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5102999806404114},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.44040000438690186},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4074999988079071},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.39149999618530273},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3734999895095825},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.3582000136375427},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.3418999910354614},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3292999863624573},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3028999865055084},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26249998807907104},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C55479107","wikidata":"https://www.wikidata.org/wiki/Q97663916","display_name":"Stochastic approximation","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C2780806968","wikidata":"https://www.wikidata.org/wiki/Q6045196","display_name":"Interaction model","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3161649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3161649","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:35320087","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35320087","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W138372711","https://openalex.org/W284777917","https://openalex.org/W1748283627","https://openalex.org/W2069849731","https://openalex.org/W2071778976","https://openalex.org/W2085534751","https://openalex.org/W2095293504","https://openalex.org/W2122467621","https://openalex.org/W2144799688","https://openalex.org/W2154047075","https://openalex.org/W2336875440","https://openalex.org/W2400109989","https://openalex.org/W2473333158","https://openalex.org/W2529358465","https://openalex.org/W2604975423","https://openalex.org/W2724643438","https://openalex.org/W2963519970","https://openalex.org/W2963730104","https://openalex.org/W2963786196","https://openalex.org/W3011813827","https://openalex.org/W3034863039","https://openalex.org/W4210962187","https://openalex.org/W6630061801","https://openalex.org/W6631043144","https://openalex.org/W6639028698","https://openalex.org/W6674412744","https://openalex.org/W6674784492","https://openalex.org/W6677101186","https://openalex.org/W6679439793","https://openalex.org/W6682089372","https://openalex.org/W6683617417","https://openalex.org/W6684588609","https://openalex.org/W6684809622","https://openalex.org/W6727968406","https://openalex.org/W6730084236","https://openalex.org/W6732234271","https://openalex.org/W6744271739","https://openalex.org/W6746343069","https://openalex.org/W6749431176","https://openalex.org/W6750424730","https://openalex.org/W6755761668","https://openalex.org/W6766682677","https://openalex.org/W6766937119","https://openalex.org/W6779955415","https://openalex.org/W6785024441","https://openalex.org/W6804468348"],"related_works":[],"abstract_inverted_index":{"Continuous-time":[0],"interaction":[1,37,151],"data":[2],"is":[3,39,75,121,145],"usually":[4],"generated":[5],"under":[6],"time-evolving":[7],"environment.":[8],"Hawkes":[9,71],"processes":[10],"(HP)":[11],"are":[12,44],"commonly":[13],"used":[14],"mechanisms":[15],"for":[16,136],"the":[17,34,56,82,110,143,157],"analysis":[18],"of":[19,59,99,113,125,142],"such":[20],"data.":[21],"However,":[22],"typical":[23],"model":[24,86],"implementations":[25],"(such":[26],"as":[27],"e.g.,":[28],"stochastic":[29,68,132],"block":[30],"models)":[31],"assume":[32],"that":[33,156],"exogenous":[35,69,83],"(background)":[36],"rate":[38,58,70,119],"constant,":[40],"and":[41,102],"so":[42],"they":[43],"limited":[45],"in":[46,55,81],"their":[47],"ability":[48],"to":[49,77,106,109],"adequately":[50],"describe":[51],"any":[52],"complex":[53],"time-evolution":[54],"background":[57,118],"a":[60,67,91,131],"process.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,154],"introduce":[66,130],"process":[72],"(SE-HP)":[73],"which":[74],"able":[76],"learn":[78],"time":[79],"variations":[80],"rate.":[84],"The":[85,116,140],"affiliates":[87],"each":[88],"node":[89],"with":[90,95],"piecewise-constant":[92],"membership":[93,111,127],"distribution":[94],"an":[96],"unknown":[97],"number":[98],"changepoint":[100],"locations,":[101],"allows":[103],"these":[104,126],"distributions":[105,112],"be":[107],"related":[108],"interacting":[114],"nodes.":[115],"time-varying":[117],"function":[120],"derived":[122],"through":[123],"combinations":[124],"functions.":[128],"We":[129],"gradient":[133],"MCMC":[134],"algorithm":[135],"efficient,":[137],"scalable":[138],"inference.":[139],"performance":[141],"SE-HP":[144,158],"explored":[146],"on":[147],"real":[148],"world,":[149],"continuous-time":[150],"datasets,":[152],"where":[153],"demonstrate":[155],"strongly":[159],"outperforms":[160],"comparable":[161],"state-of-the-art":[162],"methods.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2022-04-03T00:00:00"}
