{"id":"https://openalex.org/W4321765220","doi":"https://doi.org/10.1162/neco_a_01572","title":"Multistream-Based Marked Point Process With Decomposed Cumulative Hazard Functions","display_name":"Multistream-Based Marked Point Process With Decomposed Cumulative Hazard Functions","publication_year":2023,"publication_date":"2023-02-24","ids":{"openalex":"https://openalex.org/W4321765220","doi":"https://doi.org/10.1162/neco_a_01572","pmid":"https://pubmed.ncbi.nlm.nih.gov/36827592"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_01572","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01572","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","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":"https://openalex.org/A5073076975","display_name":"Hirotaka Hachiya","orcid":"https://orcid.org/0000-0003-3748-4101"},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hirotaka Hachiya","raw_affiliation_strings":["Graduate School of System Engineering, Wakayama University, Sakaedani 930, Wakayama-city, Wakayama 640-8510, Japan hhachiya@wakayama-u.ac.jp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of System Engineering, Wakayama University, Sakaedani 930, Wakayama-city, Wakayama 640-8510, Japan hhachiya@wakayama-u.ac.jp","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034813704","display_name":"Sujun Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Sujun Hong","raw_affiliation_strings":["Graduate School of System Engineering, Wakayama University, Sakaedani 930, Wakayama-city, Wakayama 640-8510, Japan hong.sujun@g.wakayama-u.jp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of System Engineering, Wakayama University, Sakaedani 930, Wakayama-city, Wakayama 640-8510, Japan hong.sujun@g.wakayama-u.jp","institution_ids":["https://openalex.org/I75198481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5034813704","https://openalex.org/A5073076975"],"corresponding_institution_ids":["https://openalex.org/I75198481"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03000043,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"4","first_page":"699","last_page":"726"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.9977999925613403,"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":0.9977999925613403,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9379000067710876,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T12417","display_name":"Morphological variations and asymmetry","score":0.9370999932289124,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"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/point-process","display_name":"Point process","score":0.7612805366516113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7043958902359009},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5995428562164307},{"id":"https://openalex.org/keywords/hazard","display_name":"Hazard","score":0.5961241126060486},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5901274681091309},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5721175074577332},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5522395372390747},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5363321304321289},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5216108560562134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49589189887046814},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4262728691101074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3984144330024719},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3641692101955414},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17373448610305786},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1184237003326416}],"concepts":[{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.7612805366516113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7043958902359009},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5995428562164307},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.5961241126060486},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5901274681091309},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5721175074577332},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5522395372390747},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5363321304321289},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5216108560562134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49589189887046814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4262728691101074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3984144330024719},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3641692101955414},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17373448610305786},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1184237003326416},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/neco_a_01572","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01572","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},{"id":"pmid:36827592","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36827592","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":"Neural computation","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.550000011920929,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G1195875865","display_name":"Fusion of Deep Learning and Statistical Modeling for Image Transformation Methods for Natural Event Forecasting","funder_award_id":"20K11863","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2028944227","https://openalex.org/W2612690371","https://openalex.org/W2914074791","https://openalex.org/W2945799318","https://openalex.org/W2999905431","https://openalex.org/W3124104534","https://openalex.org/W6731714541","https://openalex.org/W6736654715","https://openalex.org/W6751333561","https://openalex.org/W6755125552","https://openalex.org/W6757012226","https://openalex.org/W6762922688","https://openalex.org/W6774057418","https://openalex.org/W6785324338","https://openalex.org/W6996114663"],"related_works":["https://openalex.org/W2046435967","https://openalex.org/W4231775656","https://openalex.org/W1605128151","https://openalex.org/W2225046392","https://openalex.org/W2383646825","https://openalex.org/W2371018915","https://openalex.org/W2354191502","https://openalex.org/W4230044405","https://openalex.org/W4387389613","https://openalex.org/W1586180564"],"abstract_inverted_index":{"When":[0],"applying":[1],"a":[2,6,25,41,57,95],"point":[3,36,68,99],"process":[4,100],"to":[5],"real-world":[7,129],"problem,":[8],"an":[9],"appropriate":[10],"intensity":[11,52],"function":[12,44,53],"model":[13],"should":[14],"be":[15],"designed":[16],"based":[17],"on":[18],"physical":[19],"and":[20,79,108,128],"mathematical":[21],"prior":[22],"knowledge.":[23],"Recently,":[24],"fully":[26,96],"trainable":[27,97],"deep":[28,113],"learning-based":[29],"approach":[30],"has":[31],"been":[32],"developed":[33],"for":[34,102,106],"temporal":[35],"processes.":[37],"In":[38],"this":[39,62,91],"approach,":[40,63],"cumulative":[42],"hazard":[43],"(CHF)":[45],"capable":[46],"of":[47,50,67,73,84,120],"systematic":[48],"computation":[49],"adaptive":[51],"is":[54,86],"modeled":[55],"in":[56,61],"data-driven":[58],"manner.":[59],"However,":[60],"although":[64],"many":[65],"applications":[66],"processes":[69],"generate":[70],"various":[71],"kinds":[72],"information":[74,83],"such":[75],"as":[76],"location,":[77],"magnitude,":[78],"depth,":[80],"the":[81,118,121],"mark":[82,109],"events":[85],"not":[87],"considered.":[88],"To":[89],"overcome":[90],"limitation,":[92],"we":[93],"propose":[94],"marked":[98],"method":[101,123],"modeling":[103],"decomposed":[104],"CHFs":[105],"time":[107],"prediction":[110],"using":[111],"multistream":[112],"neural":[114],"networks.":[115],"We":[116],"demonstrate":[117],"effectiveness":[119],"proposed":[122],"through":[124],"experiments":[125],"with":[126],"synthetic":[127],"event":[130],"data.":[131]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}